Transcript pps
Slide 1
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 2
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 3
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 4
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 5
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 6
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 7
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 8
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 9
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 10
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 11
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 12
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 13
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 14
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 15
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 16
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 17
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 18
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 19
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 20
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 21
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 22
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 23
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 24
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 25
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 26
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 27
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 28
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 29
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 30
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 31
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 32
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 33
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 34
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 35
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 36
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 37
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 38
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 39
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 40
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 41
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 42
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 43
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 44
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 45
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 46
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 47
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 48
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 49
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 50
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 51
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 52
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 53
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 54
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 55
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 56
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 57
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 58
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 59
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 60
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 61
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 62
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 63
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 64
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 65
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 66
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 67
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 68
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 69
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 70
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 71
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 72
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 73
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 74
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 75
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 76
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 77
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 78
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 79
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 80
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 81
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 82
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 83
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 84
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 85
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 86
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 87
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 88
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 89
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 90
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 91
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 92
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 93
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 94
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 95
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 96
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 97
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 98
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 99
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 2
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 3
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 4
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 5
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 6
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 7
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 8
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 9
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 10
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 11
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 12
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 13
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 14
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 15
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 16
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 17
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 18
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 19
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 20
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 21
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 22
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 23
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 24
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 25
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 26
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 27
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 28
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 29
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 30
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 31
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 32
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 33
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 34
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 35
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 36
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 37
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 38
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 39
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 40
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 41
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 42
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 43
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 44
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 45
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 46
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 47
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 48
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 49
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 50
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 51
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 52
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 53
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 54
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 55
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 56
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 57
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 58
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 59
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 60
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 61
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 62
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 63
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 64
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 65
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 66
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 67
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 68
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 69
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 70
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 71
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 72
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 73
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 74
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 75
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 76
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 77
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 78
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 79
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 80
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 81
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 82
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 83
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 84
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 85
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 86
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 87
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 88
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 89
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 90
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 91
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 92
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 93
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 94
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 95
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 96
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 97
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 98
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy
Slide 99
Structural proteomics lecture 4:
Biophysical dissection of protein complexes
• “Protein complexes and their
interactions are the basis of all biology”
• True understanding of cellular
processes requires understanding of the
underlying molecular mechanisms
• BUT… molecules should not be seen in
isolation!
T cell
cell Surface
Surface Organisation
Composition
T
e.g. a key complex: the T cell receptor
What’s in the complex – how is it
assembled? Need to understand
this to know how it can signal.
How does it bind its ligand – how is it
so specific? What is the effective
range of affinities? etc etc
or
One ab per complex
Dimer of heterodimers
Biophysical in vitro techniques to dissect
protein complexes & their interactions
1.
2.
3.
4.
5.
AUC
SPR
ITC
FRET / BRET
Single molecule microscopy (?)
1. AUC
(Analytical Ultracentrifugation)
What is Analytical Ultracentrifugation for?
The measurement of properties of molecular species such
as mass and shape constants and their alteration with
concentration (e.g. during self-association or multicomponent assembly)
Why use Analytical Ultracentrifugation ?
The possible mechanisms of protein complex function will
often be limited by its organisation: AUC can assess
complex size and degree of self-association as well as
giving a measure of monodispersity of in vitro reagents.
Ultracentrifugation
• Preparative
– separate complex mixtures
– fractionate cellular components
– density gradients to separate by molecular mass
• Analytical
– sedimentation equilibration
– sedimentation velocity
• Thermodynamic
• Hydrodynamic
• Absolute MW
• Relative MW
• Shape independent
• Molecular shape
• Aggregation
• Aggregation behavior
• Protein-protein interactions
Theory: The Svedberg equation
• Consider a particle m in a
centrifuge tube filled with a
liquid.
• The particle (m) is acted on
by three forces:
– FC: the centrifugal force
– FB: the buoyant force
(Archimedes principle)
– Ff: the frictional force
between the particle and
the liquid
• Will reach constant velocity
where forces balance:
Theory: The Svedberg equation
• Define s,
the sedimentation coefficient:
s=
• s is a constant for a given particle/solvent, has units of
seconds, but use Svedberg (S) units (10–13 s).
• Cytochrome s=1S, ribosome s=70S, composed of 50S
and 30S subunits (s does not vary linearly with Mr)
• Values for most biomolecules betwwen 1 and 10000 S
Theory: The Svedberg equation
f
S=
RT
ND
D = diffusion coefficient, N = Avogadro’s number
s
m 0 (1 )
Mr
RT ND
or
RTs NDm 0 (1 )
RTs
)
D (1
(Because Mr = Nm0)
• Therefore can directly determine Mr in solution by
measuring physical properties of the particle (s and v)
under known experimental conditions (D, T and ),
• c.f. PAGE, chromatography – comparative & non-native
Equipment
• E.g. Beckman XL-A (or XL-I)
analytical ultracentrifuge
• Samples loaded into special centrifuge
cells with transparent windows for
optical measurements.
• The distribution of solute molecules during the
experiment is monitored by an optical system. The
cells are scanned across their entire radius and
data automatically collected for subsequent
analysis
1A. Equilibrium sedimentation
Meniscus
Cell bottom
• Moderate centrifuge speed • Non-linear curve fitting can
rigorously determine:
• After sufficient time, an
equilibrium is reached
– the solution molecular
between sedimentation &
weight
diffusion, resulting in a
– association state
montonic solute distribution
– equilibrium constant for
across the cell
complex formation
Equilibrium sedimentation –
monomer-dimer equilibrium
• Data for transferrin at three
loading concentrations.
All three datasets were fit
simultaneously to a
monomer-dimer equilibrium
model. The fit returned a Kd
of about 100 mM for the
dimerization.
• The relatively small and
randomly distributed
residuals indicate that the
model provided a good fit to
the data.
Experimental considerations
• Wavelength for detection (280nm – 230nm)
• Choice of buffer - typically PBS, pH 7.0, 200 mM NaCl
– Tris buffer can be used at 280 nm. (interferes at 230 nm)
– If a reducing agent is needed, b-mercaptoethanol is
better than dithiothreitol as it doesn’t absorb at 280 nm.
• Protein concentration
– Ensure detection at wavelength chosen
– Sufficient range to detect association
• Temperature
• Equilibrium time – typically 18-24 hours
– depends on length of cell, viscoity etc.
• Rotor Speed
Rotor speed
selection chart
Data collection
• Sample preparation: Dialyze against buffer, scan from 350 to 200 nm
to test for contaminants & test for aggregation by micro-centrifugation.
• Sample loading: Reference cell side by side with sample, with slightly
more volume (105ul c.f. 100ul). If using multiple chambers, place most
concentrated sample closest to the center of rotation.
• Calibration: radial & wavelength calibration on first use or rotor change
• Experiment: set vacuum, temperature & speed and read every 2-3
hours, two identical readings = equilibrium, repeat at further speeds.
• Stability test: check equilibrium again after an additional 10-12 hour spin
• Baseline: Repeat reading at very high speeds when all solute at base.
12 mm
3 mm
Data analysis
•
•
•
•
Editing the raw data
Baseline correction
Test mass recovery
Data modeling
Editing raw data
• Remove the
meniscus
• Remove the
bottom of the
cell
• Remove the
bumps and
spikes
Baseline correction
• Deplete all macromolecular components using v. high speeds
• Record baseline absorbance
• Subtract this from observed absorbances
Test mass recovery
Initial absorbance x volume of the sample = total mass
• Integration of experimental plot of absorbance vs squared
radial position is used to monitor recovery of total mass
• Large loss of mass after an increase in the speed suggests
occurrence of aggregation/precipitation
• An increase in recovery at higher speed is suggestive of
breakdown of the molecules
Data modeling
• A plot of ln(c) vs r2
should be a straight
line with a slope
proportional to
molecular weight
Single ideal homogeneous species
Mp(1- ) =
d ln(c) 2RT
d r2 w2
Curvature in log plots
• Indicates heterogeneity of the system
• Arises from self-association of protein
• Slope at any radial position is proportional to the weight
average molecular weight
Residuals
• Start of with a single component model and execute a fit
• Ideally you should have a residuals like in panel (a).
• If residuals systematically vary, try another model!
Lymphotactin
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
19K
26K
31K
40K
little or no curvature
obvious curvature –
mass also lost after spin
Direct fitting:
Self association at 10 ºC & 200 mM NaCl
Effect of salt & temperature on aggregation
10 ºC, 200 mM NaCl
40 ºC, 100 mM NaCl
Affinity/avidity and function in costimulation
Bivalency:
stabilizes
complexes
~100-fold
But are B7-1
and B7-2 really
different
(proposed from
crystals) ?
Importance of valency:
Dimerization of sB7-1
Mw,app(Da/104)
6
5
4
3
2
sB7-1
0
1.0
2.0
Protein concentration (mg/ml)
Importance of valency:
sB7-2 & LICOS are monomers
80
80
sLICOS
sB7-2
60
Mw(kDa)
Mw(kDa)
60
40
40
20
20
0
0
0
1
2
3
4
Concentration (mg/ml)
0
1
2
3
4
Concentration (mg/ml)
1B. Velocity sedimentation
• High centrifuge speed
• Non-linear curve fitting can
rigorously determine:
• Forms a sharp boundary
between solute depleted
– number of mass species
region (at top) and a region
– molecular weight
of uniform solute concn
– shape information for a
(at bottom)
molecule of known mass
• The concentration gradient
(dc/dr) defines the boundary
position
Velocity sedimentation - data analysis
• sedimentation coefficient (s) is the rate at which the
sedimentation boundary moves
– depends on the molecular weight & shape
– globular (more spherical) protein has the largest
sedimentation coefficient for a given molecular weight
– unfolded or elongated proteins experience more friction -smaller sedimentation coefficients
• diffusion coefficient is related to minimum width of the
sedimentation boundary, multiple species broaden the
boundary beyond effects of diffusion alone
Velocity sedimentation - data analysis
g(s*) distribution
Velocity sedimentation - data analysis
• This antibody gives only one distinct peak, centered
at s ~ 6.5 S, which corresponds to the native
antibody 'monomer‘. This is low for a 150 kDa
species due to its highly asymmetric 'Y' shape.
• However, a more detailed analysis quickly reveals
that this sample is not homogeneous. The red curve
is a fit of these data as a single species. It does not
match the data in the region from 8-12 S, indicating
the presence of some multimer.
• From the width of the main peak we can calculate
the apparent diffusion coefficient (D) of the
monomer. From the ratio of s to D we can calculate a
mass of 151 kDa for this species, which matches the
known value well within 3-5% error expected for
masses determined in this fashion.
Mr
RTs
D (1 )
The example of SLAM (CD150)
• Claimed to self-associate with nM Kd raising serious problems
for all known models of cell surface protein interactions.
• Equilibrium data couldn’t be fitted – concentrations too high!
• Velocity data confirmed shape of complex and approximate
strength of association
2. SPR / BIAcore
(Surface Plasmon Resonance)
What is Surface Plasmon Resonance for?
The accurate measurement of the properties of intermolecular interactions without a wash step.
(Contrast with interaction screens and crude measurements
of bond strength e.g. AUC or washed systems like ELISA)
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
The range of affinities seen for
transient interactions at the cell surface
Selectins
Inactive LFA-1
fully active LFA-1
fully active Mac-1
SLAM
CD28
CD8
TCR
CD4
rCD2 hCD2 KIR
1000
100
10
3D Kd (mM)
CTLA-4 Ab:Ag
1
0.1
Why use Surface Plasmon Resonance?
A full understanding of the function of proteins requires
accurate knowledge of the nature of their interactions.
Example: Costimulation vs. Inhibition (again!)
B7.1 and B7.2 both bind to CD28 and CTLA-4.
BUT
B7.2 & CD28 are constitutively expressed, others on activation
B7.1 is dimeric, B7.2 is not
CD28, although dimeric, is monovalent
CTLA-4 binds its ligands much more strongly than CD28 BIAcore
B7.1 binds its ligands more strongly than B7.2
RESULT: The inhibitory B7.1:CTLA-4 complex is ~1000 times
more stable than the costimulatory B7.2:CD28 complex.
Principle of Surface Plasmon Resonance
Angle of ‘dip’ affected by:
1) Wavelength of light
2) Temperature
3) Refractive index n2
Dip in light
intensity
Surface Plasmon Resonance in the BIAcore
Basic Idea…
NB 4 channels (‘flow cells’) per ‘chip’
2 steps:
• Immobilisation:
Stick something (or up to 3 things) to the chip
(NB also stick a control down)
• Inject analyte:
Inject something else and see if it binds, how much
binds and how fast it binds
Immobilisation
2 Main options:
• Direct:
Covalently bind your molecule to the chip
• Indirect:
First immobilise something that binds your molecule
with high affinity e.g. streptavidin / antibodies
Direct:
Indirect:
Immobilisation: Carboxymethyl binding
CM5
Sensor
Chip
N.B. Carboxymethyl groups are on a dextran matrix:
This is negatively charged =>
Need to do a “preconcentration” test to determine
optimum pH for binding (molecule needs to be +ve)
Immobilisation: Other sensor chips
SA
NTA
HPA
Sensorgrams (raw data)
pH: 4.0 4.5 5.0 5.5
A
BC
D
15,400 RU
Pre-concentration:
Immobilisation:
An antibody was diluted in buffers
of different pH and injected over
an non-activated chip.
Maximum electrostatic attraction
occurs at pH 5
A. Inject 70ml 1:1 EDC:NHS
B. Inject 7ml mAb in pH5 buffer
(in this case @370mg/ml)
C. Inject 70ml Ethanolamine
D. Inject 30ml 10mM Glycine pH2.5
Sensorgrams – ligand binding
“Specific” Binding
•
•
•
•
Each chip has four ‘flow-cells’
Immobilise different molecules in each flow-cell
Must have a ‘control’ flowcell
‘Specific binding’ is the response in flow-cell of
interest minus response in the control flowcell
Specific response in red flowcell
Response in control / empty flowcell due to
viscosity of protein solution injected –
therefore ‘control’ response DOES increase
with concentration (this is NOT binding!!)
Measured
response
Is it
specific?
Equilibrium Binding Analysis
N.B. Measurement of affinities etc. should usually be done at physiological
temperature (i.e. 37°C), although this is more difficult.
Sometimes 25°C data can be used to compare fold differences in binding or
to test for any binding at all (i.e. specificity studies).
1200
R.U.
900
600
300
0
0
100 200 300 400 500 600 700
Time (s)
Equilibrium Binding Analysis - continued
Scatchard plot: rearrangement
of binding isotherm to give a
linear plot. Not so good for
calculating Kd, as gives undue
weight to least reliable points
(low concentration)
Bound
[ A]
Binding curve can be fitted with
a Langmuir binding isotherm
(assuming a 1:1 binding with a
single affinity)
Bound
R Max [ A ]
[ A] K d
R Max
Kd
Bound
Kd
Plot Bound/Free against Bound
Gradient = 1/Kd
Kinetics
Harder
Case:
2B4
binding
CD48
Potential pitfalls
• Protein Problems:
Aggregates (common)
Concentration errors
Artefacts of construct
• Importance of controls: Bulk refractive index issues
Control analyte
Different levels of immobilisation
Use both orientations (if pos.)
• Mass Transport:
Rate of binding limited by rate of
injection: kon will be underestimated
• Rebinding:
Analyte rebinds before leaving chip
koff will be underestimated
Last two can be spotted if measured kon and koff vary with
immobilisation level (hence importance of controls)
Less common applications
1. Temperature dependence of binding
van’t Hoff analysis:
G RT ln( K a ) H T S
H 1 S
ln( K a )
R
R T
Gradient
Intercept
Less common applications
1. Temperature dependence of binding
Non-linear
van’t Hoff analysis:
G H vH ,T 0 T S vH ,T 0 C p , vH (T T 0 ) T C p , vH
T
ln
T0
Less common applications
2. Combination with mutagenesis
Binding of CD2 by CD48 mutants at 25°C (WT Kd = 40mM)
Immobilised
Ligand
Immobilisation
Level
(RU)
WT CD48-CD4
2000
L35A
1950
R87A
1900
Q30K
1950
Q40R
2000
E55R
2000
Q30R
rsCD2
Replicate concentration
range (mM)
1
0.6-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
10-320
2
0.8-407
3
0.7-348
1
1.2-320
2
0.8-408
3
0.8-409
1
20-320
2
0.8-408
3
1.6-409
1
1.2-320
2
0.8-408
3
0.8-409
Q40K
Kd (mM)
30
49
46
1200*
1700*
1500*
33500*
15100*
3760*
29
37
36
411
431
474
13
18
19
Mean Kd
(mM)
s.e.m.
(mM)
41.7
5.9
1455*
144.4
Reduce
/ abolish binding
R87A
Do
not affect binding
17453.3* 8665.5
Not yet tested
34.0
2.5
438.7
18.6
16.7
1.9
Less common applications
3. Estimation of valency
Less common applications
3. Screening
Newer BIAcore machines are capable of high throughput
injection. With target immobilised, many potential
partners / drugs can be tested for binding.
4. Identification of unknown ligands
Mixtures e.g. cell lysates, tcs, food samples etc. can be
injected over a target and bound molecules can then be
eluted into tandem mass spectroscopy for identification.
One last warning: take care
CD48 binding to
immobilised CD2
(van der Merwe et al.)
What
a lot
of people would have used
Correct
result
(straight out of the freezer)
3. ITC
(Isothermal Titration Calorimetry)
What is Isothermal Titration Calorimetry for?
The direct measurement of heat released from a reaction
(e.g. a binding event) allowing the calculation of
thermodynamic parameters (enthalpy & entropy)
Why use Isothermal Titration Calorimetry ?
The thermodynamics of an interaction can give clues to the
mechanisms involved. ITC also has the advantage of
testing affinity in solution using unlabelled protein (but lots
of it!!).
Isothermal Titration Microcalorimetry:
Using the heat of complex formation to
report on a binding interaction.
The Basic Experiment:
1. Fill the upper syringe with ligand at high
concentrations.
2. Fill the larger lower reservoir with protein
at a lower concentration.
3. Titrate small aliquots of ligand into protein.
4. After each addition, the instrument returns
the reservoir temperature to the
temperature of the control cell and
measures the heat required to cause this
change.
5. Typically, subtract appropriate blank
titrations (ligand into buffer & buffer into
protein) to control for heats of dilution.
Data Analysis
• Get a plot of heat (mJ or mCal) / s following each injection,
integrate each peak for total heat released and plot against
concentration of protein injected – binding isotherm.
c = concn / Kd
Data Analysis – e.g. of B7-1 & CTLA-4
kcal/mole of injectant
• Curve fitting gives values for H (enthalpy) and G (Gibbs
free energy, related to affinity) – from these one can also
calculate S (entropy).
0
-4
H = -11.6
G = -8.9
TS = -2.7
kcal/mol-1
-8
-12
0
1
2
3
4
molar
ratio
Calculating heat capacity
H and S are not constant with temperature, hence direct
measurement by ITC is better than deriving them from
binding data across several temperatures (e.g. by SPR)
• Relationship of DH to temperature can be used to calculate
heat capacity change on binding (Cp)
•
TCR recognition
Willcox et al. (1999) Immunity 10:357
TCR recognition
Willcox et al. (1999) Immunity 10:357
4. FRET / BRET
(Forster / Bioluminescence
resonance energy transfer)
What is FRET?
• Förster Resonance Energy Transfer
– Fluorescence if both Donor and Acceptor are
fluorescent
• Radiation-less energy transition between
a Donor and Acceptor occurring finite
probability based on proximity
• Energy is transferred through the resonant
coupling of the dipole moments of the
Donor & Acceptor
The beginning…
• Theodor Förster, 1940s
– proposed a mathematical law for dependence of
fluorescence decay of donor (D) on the
concentration of acceptor (A), assuming a dipoledipole interaction in solution
(J.Phys.Chem. 1965, 69, 1061-1062)
Exponential decay for one Donor molecule
Impact of FRET
• After the initial fuss about the validity of
Förster’s derivations, little else.
• Resurgence in past several years, especially
in biology/biochemistry/biophysics thanks to:
– FRET capable spectral GFP mutants
– Engineering of peptides with novel fluorescent
reagents
– Ability to couple this phenomenon to different
imaging techniques
– AND the need to “see” finer details
Power of FRET
• Probe macromolecular interactions
– Interaction assumed upon fluorescence
decay
• Study kinetics of association/dissociation
between macromolecules
• Estimation of distances (?)
• In vitro OR on live cells
• Single molecule studies
FRET
Effects of FRET
• Intensity of Donor decreases
• Sensitized fluorescence of Acceptor
appears upon Donor excitation
• Lifetime of Donor excited stated decreases
• Polarization anisotropy increases
• Taking advantage of these points…
– Curr. Opin. Immun. 2004, 16, 418-427
FRET Efficiency (E)
Measuring FRET efficiency
• Measure acceptor emissions – can
be measured in solution, no
confoccal but background high due
to overlap of frequencies.
• Measure increase in donor
emissions after photobleaching
acceptor - usually done with high
power laser setting in confocal on
cell surface molecules.
• FLIM (fluorescence lifetime
imaging) – measure lifetime of
donor excited state in presence &
absence of acceptor.
Live cell FRET imaging
Does CD4 specifically associate with the TCR/CD3 complex
on triggering?
Non-specific peptide
Specific peptide
• * marks contacts between cells.
• High FRET signal between CD4 and CD3 when correct
antigen is present but not with non-specific antigen.
BRET: Bioluminescence Resonance Energy Transfer
DeepBlueC
hf1
hf2
GFP2
Luciferase >10nm
BRET analysis of human B7-1 dimerization
at the cell surface
B7-1luc
YFP
luc
substrate
B7-1YFP
hu2 (530 nm)
hu1 (470 nm)
B7-1luc:B7-1YFP
B7-1luc
CTLA-4luc:CTLA-4YFP
B7-1luc:CTLA-4YFP
BRET Theory
r
BRET 1
R
0
6
R0
1
BRET vs. FRET
BRET analysis can be achieved at physiological levels of
protein expression
No problems with photobleaching or photoconversion
seen in FRET techinques
Both methods involve the same physical processes and
so can be analysed in a similar manner
BRET cannot be used in microscopy-based techniques
such as FRAP or FLIP, or FACS-based analysis
Construction of Fusion Proteins
The gene of interest is fused to both luciferase (donor)
and GFP (acceptor) in two separate vectors
A positive control is used to determine maximal BRET
B7-Family BRET
Energy transfer can occur solely by random interactions
Quantitative (F)RET Analysis
Decreasing
As more acceptors
the numbers
are present
of donors
at the
does
cellnot
surface,
affect BRET
increases
average
as distance
more donors
between
are paired
donorswith
andan
acceptor
acceptor, to the
pointmolecules
where every donor is productively paired (saturation)
Dimer Interactions
Random Interactions
Quantitative BRET Analysis
The relative ratio of the luciferase (donor) and GFP
(acceptor) can be systemically varied at a constant total
surface expression
Energy transfer from oligomeric interactions are
predicted to depend on this ratio in a hyperbolic manner
Random interactions should be insensitive to these
changes in ratio
BRET Method
HEK-293T
pGFP-N3
FuGene
prLuc-N3
DeepBlueC
Comparison to T cell surface molecules
with known oligomerisation status!
Strong dimers
Weak dimer
Monomers
T Cell Interactions
Goodness of fit to the two alternative models clearly
demonstrates CD86 is monomeric
Ligand binding causes specific increase in dimerisation
Specific ligand engagement can be observed when
receptor is presented in solution or cell-surface bound
0.5
BRET Ratio
0.4
0.3
0.2
hCD80
hCD80
hCD86
hCD86
0.1
+
+
CTLA-4
CTLA-4
CTLA-4
CTLA-4
0.0
0
1
2
3
GFP / Rluc
4
5
GPCRs Are Likely To Be Monomeric
Two GPCRs exhibit no dependence on the
acceptor:donor ratio
Equivalent BRET is seen when GPCR is co-expressed
with CD2, demonstrating random interaction
A BRET survey of the T cell surface
The majority of T cell surface molecules are monomeric
at the cell surface
5. Single molecule microscopy
Single Molecule Spectroscopy
T cell activation occurs at the level of single molecules,
i.e., TCR complex binding to pMHC
There are almost no methods to probe cell surface to
this level of detail in living cells, or to deal with
complexes larger than the 10nm limit of FRET/BRET
Need to understand the interactions that occur in order
to build a realistic model of T cell activation
New therapeutic agents may rely more and more on
targetting our immune response by precisely altering
these interactions
Single Molecule Spectroscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Single Molecule Method
Antibodies are fragmented to Fabs and labelled with
bright fluorescent dyes, Alexa 488 and Alexa 647
T cell hybridomas are incubated with labelled Fabs to
saturation
Two lasers are focussed on the apical membrane of cell
Movement of Fab-labelled molecules can be recorded in
real time to single molecule precision
Single Molecule Confocal
Microscopy
10 fl (10-8ml)
0.25mm2 of
cell surface
Controls for Coincidence Detection
No peaks are observed without Fab labels
Fab binding was specific to Vb8 TCR
Fluorescence was only detected at the proximal and
apical membranes
PFA-fixed cells displayed constant fluorescence
Changes in laser power did not affect results
TCR complex diffused at expected rate
Blocking internalisation did not alter signal observed
Coincident events can be detected
Molecules in complex have higher coincidence
TCR stoichiometry at the cell surface
After background subtraction…
TCR:TCR
coincidence
is identical to CD2:CD2
CD3:TCR
and CD3:CD3
are significantly higher
Total Internal Reflection Microscopy
Extension of coincidence detection using TIR
microscopy, allowing tracking of molecules in real time
Models of T cell activation can be directly tested
Techniques you may need…
•
•
•
•
•
Probing molecular interactions: SPR
Probing homodimeric interactions: AUC
Probing size & shape of complexes: AUC
Probing detailed thermodynamics: ITC
Probing oligomerisation state or associations
in cell or on their surface: FRET / BRET
• Probing for longer range associations or
assocaitions between things you can’t make:
single molecule microscopy