Transcript Multicolor course-HTM - Maeckerlab Weblog

Multicolor Flow Cytometry
Workshop
Holden Maecker, PhD
Learning Objectives
• Explain the critical aspects of digital and multicolor flow cytometry
that make it different from traditional analog flow cytometry with 1–4
colors
• Describe the role of instrument configuration in the performance of
multicolor flow cytometry
• Perform instrument QC using BDTM Cytometer Setup and Tracking
beads, and understand the use of baseline and application settings
in BD FACSDivaTM software
• Design a robust multicolor reagent panel, understanding the role of
spillover, tandem dyes, and antibody titration
• Create appropriate controls for a multicolor experiment, and be able
to find and correct potential problems in multicolor data
Schedule: Day 1
9:00–10:30
I. Introduction, review of basic concepts
10:30–10:45
Break
10:45–11:45
II. Digital and multicolor flow cytometry
Exercise 1: Adjusting biexponential displays
12:00–1:00
Lunch
1:00–2:00
III. Instrument setup, optimization, and QC
Exercise 2: Determining stain index and spill index
2:00–4:00
Acquisition of data:
•
•
•
•
Instrument characterization using CS&T
Baseline and application settings determination
Compensation using BD™ CompBeads
8-color stained PBMCs
Schedule: Day 2
9:00–10:00
IV. Design and optimization of multicolor panels:
• Selection of fluorochromes
• Matching fluorochromes with antibody specificities
• Determining application-specific settings
Demonstration: Visualizing data on a virtual cytometer
10:00–12:00
Data analysis in BD FACSDiva software
12:00–1:00
Lunch
1:00–2:30
V. Controls and Data QC
Exercise 3: Finding and correcting a spillover problem
2:30–2:45
Break
2:45–4:00
Review and summary, discussion of participant issues
Multicolor Flow Cytometry Workshop:
I. Review of Flow Cytometry Basics
Outline
• Definitions, what can be measured by flow cytometry
• Fluidics: Sheath and sample streams, flow cells, sorting
• Optics: Lasers, filters
• Electronics: PMTs, signal processing
• Fluorochromes: Spectra, spillover
• Data analysis: FCS files, gating, statistics
Definitions
• Flow cytometry: The study of cells as they move
in fluid suspension, allowing multiple
measurements to be made for each cell.
• FACSTM: Fluorescence-activated cell sorting
What Measurements Can Be Made?
• Forward scatter (FSC): Proportional to cell size
• Side scatter (SSC): Proportional to cell granularity
• Fluorescence:
-
Binding of fluorescent-labeled antibodies
Ca++-sensitive dyes within cells
Fluorescent proteins expressed by cells
Binding of DNA dyes
Scatter Profile of Lysed Whole Blood
400
600
Granulocytes
Monocytes
200
Side Scatter
800
1000
Largest and most
granular population
Lymphocytes
0
Smallest and least
granular population
0
200
400
600
800
Forward Scatter
1000
Negative control histogram
PE
Number of Events
Fluorescence Data Display
FITC Fluorescent Intensity 
FITC
Major Components of a Flow Cytometer
• Sample injection port
• Sheath and waste reservoirs
• Flow cell
• Laser(s)
• Optical filters
• Photomultiplier tubes ( PMTs ) or photodiodes
• Signal processor
Cytometer Fluidics Create Laminar Flow
Flow cell
Sample stream
Sheath stream
Laser beam
Cell
Cell Sorting
Multicolor Experiment Cytometer Configuration
Longpass filter
Bandpass
filter
PMT
Background and Autofluorescence
All cells have a certain level of background fluorescence
due to:
• Autofluorescence from pigments and fluorescent moieties on
cellular proteins
• Non-specifically bound antibodies and free antibody in the
sample stream
The level of autofluorescence varies with the wavelength of
excitation and collection:
• Highest in FITC, PE detectors
• Lowest in far red (APC, Cy™7) detectors
Fluorescence Sensitivity
Detection Efficiency (Q): The number of photoelectrons
generated per molecule of fluorophore
• Dependent upon fluorophore, laser, filters, PMT sensitivity, voltage
gain setting, etc.
Background (B): Non-specific signal intrinsic to the system
• Dependent upon autofluorescence, unbound fluorophore, ambient
light, etc.
Common Fluorophores for Ab Conjugation
FLUOROCHROME
Type of molecule
Typical excitation laser
Approximate emission
peak
Fluorescein
isothyocyanate (FITC)
Small organic
488 nm
518 nm
Alexa Fluor® 488
Small organic
488 nm
518 nm
Phycoerythrin (PE)
Protein
488 or 532 nm
574 nm
PE-Texas Red®
Protein tandem
488 or 532 nm
615 nm
PE-Cy™5
Protein tandem
488 or 532 nm
665 nm
Peridinin chlorophyll
protein (PerCP)
Protein
488 or 532 nm
676 nm
PerCP-Cy™ 5.5
Protein tandem
488 or 532 nm
695 nm
PE-Cy™ 7
Protein tandem
488 or 532 nm
776 nm
Allophycocyanin (APC)
Protein
633 nm
659 nm
Alexa Fluor® 647
Small organic
633 nm
667 nm
Alexa Fluor® 700
Small organic
633 nm
718 nm
APC-Cy™ 7 or APC-H7
Protein tandem
633 nm
784 nm
Pacific BlueTM
Small organic
405 nm
454 nm
AmCyan
Protein
405 nm
487 nm
Fluorescence Spillover
Emission of FITC
in the PE channel
Compensating for Spillover
Uncompensated
Uncompensated
Compensated
Compensated
FITC mean fluorescence
---------------------------Negative
Positive
-------------------125
3,540
125
3,560
PE mean fluorescence
---------------------------Negative
Positive
-------------------185
1,650
135
135
1,650 – 185
% Spillover =
X 100
3,540 – 125
FCS Files
• FCS 2.0 and FCS 3.0 conventions
• Often referred to as list-mode files
• Contain all of the measurements (FSC-H, FSC-A,
SSC-H, SSC-A, FL1-H…) for each individual cell
processed in a given sample
Hierarchical Gating
Web Reference Tools
• BD Spectrum Viewer:
www.bdbiosciences.com/spectra
• Maecker lab weblog:
http://maeckerlab.typepad.com
(protocols, manuscripts, literature updates)
Multicolor Flow Cytometry Workshop:
II. Digital & Multicolor Flow Cytometry
Differences From Analog Instruments
• Optics: Fiber optics and octagons/trigons
• Fluidics: Optimized for high flow rates
• Electronics: Digital signal processing
PMT Octagon and Trigon
PMT
Bandpass
filter
Longpass
filter
Filter Nomenclature Conventions
Longpass (LP) filter: Allows light above a certain wavelength
to pass, reflects shorter wavelengths
• Example: 505 LP = 505 nm longpass
Bandpass (BP) filter: Allows light within a certain range of
wavelengths to pass (above and below a specified
midpoint)
• Example: 530/30 BP = 515–545 nm bandpass
Effect of Flow Rate
• Higher flow rates mean a broader sample stream ( less
precise focusing)
• Less precise focusing means less accurate fluorescence
measurement of dim populations ( population spreading)
• Higher flow rates also increase the frequency of
coincident events (can be gated out based on FSC area
vs height)
• In practice, flow rates of 8,000–12,000 events per second
are acceptable on the BD™ LSR II (vs 2,000–3,000
events per second on a BD FACSCalibur™ flow
cytometer)
Digital Signal Processing
Generates high resolution fluorescence values that can
include negative numbers
• No compression of populations at the low end of the fluorescence
scale
• More accurate representation of dim populations
Allows compensation to be performed in the software at any
time
• Uncompensated data and any associated compensation matrix are
both stored
• Compensation can be changed at any time
Peak area and peak height can both be recorded for all
parameters
Biexponential Display of Digital Data
Uncom pe ns ate d
10
5
10
A
Com pe ns ated
10
5
4
10
4
10
3
10
3
10
2
10
2
Antibody capture beads
stained with 3 levels of
an APC reagent
B
APC-Cy7 Area
Log
10 1
10 1
10
Bie xp
10
5
10
4
10 3
1
10
2
10
3
10
4
10
5
C
All populations
align correctly
0
10
10
5
10
4
1
10
2
10
3
10
4
10
5
D
10 3
0
0
10 3
10 4
10 5
APC Area
0
10 3
10 4
10 5
The transformed display
shows aligned populations
In the APC-Cy7 dimension
Spillover Affects Resolution Sensitivity
Without CD45 AmCyan
With CD45 AmCyan
CD19 FITC
Conclusions
• Optical platforms using octagons and trigons result in
more efficient light collection and flexibility in the use of
detectors and filters
• BD LSR II fluidics allow running at higher flow rates with
minimal compromise to the data
• Digital signal processing provides more accurate
representation of dim populations, and more accurate and
flexible compensation—but logarithmic data display may
not be appropriate
• More colors mean more spillover issues, with loss of
resolution sensitivity in affected detectors
Exercise 1
Adjusting biexponential displays:
1. Open the FCS file “exercise1.fcs”
2. Gate on small lymphocytes, then on double-positive events
for CD45 AmCyan vs CD3 Pacific Blue
3. From this gate, create a plot of CD4 FITC vs CD8 APC-H7
4. Turn on biexponential scaling for the x- and y-axes, and
note the changes to the plots
5. Turn on manual biexponential scaling and experiment with
various scaling factors for FITC and APC-H7, noting how
the plots change
Questions:
1. Would gating be affected by biexponential scaling?
2. Is it important to use the same scaling for all samples in an
experiment?
Multicolor Flow Cytometry Workshop:
III. Instrument Setup and QC
Outline
1. Configure your instrument
2. Characterize your instrument
3. Design your panel
4. Optimize settings for your panel
5. Run appropriate controls
6. QC your data
Outline
1. Configure your instrument
•
•
•
Number and type of lasers
Number of PMTs per laser
Choice of filters and dichroic mirrors
These choices will determine:
•
•
What fluorochromes you can use effectively
How well certain fluorochrome combinations will perform
How Do We Measure Performance?
Resolution Sensitivity
D
W1
W2
Stain Index = D / W
Where
D = difference between positive and negative peak medians
W = 2 x rSD (robust standard deviation)
An Example: Green vs Blue Lasers
• Green laser is more efficient for PE and PE tandems
• Blue laser is more efficient for FITC, PerCP, and GFP
CD127 PE
40
Stain index
35
30
25 mW green laser (532 nm)
25
100 mW blue laser (488 nm)
20
25 mW blue laser (488 nm)
15
10
5
0
300 400 500 600 700
PMT voltage
Second Example: Filters and Spillover
Outline
2. Characterize your instrument
•
•
Obtain minimum baseline PMT settings
Track performance over time
This allows you to:
•
•
Run the instrument where it is most sensitive
Be alert to changes in the instrument that might affect
performance
Automated Baseline PMT Voltage
Determination Using BD CS&T
Baseline PMTV is set by placing the dim bead MFI to equal 10X SDEN
460 V
SDEN = 20
MFI = 200
Performance Tracking
A variety of parameters can be tracked:
• Linearity, CVs, laser alignment
• PMT voltages must hit target values
Data can be visualized in Levey-Jennings plots:
FITC Channel (Blue laser)
550
PMT Voltage
525
500
475
450
425
400
10/22/04
11/11/04
12/01/04
12/21/04
01/10/05
Time
01/30/05
02/19/05
03/11/05
Exercise 2
Calculating stain index and spill index:
1. Open the FCS file “exercise2.fcs” (AmCyan Compbeads)
2. Calculate the stain index in the primary detector (AmCyan)
by determining:
[Median (positive peak)] - [Median (neg peak)]
2 x rSD (neg peak)
3. Calculate the spill index in FITC by determining the FITC
stain index as above, then calculating:
[Stain index (FITC) / Stain index (AmCyan)]
Questions:
1. What is an acceptable stain index?
2. How high can the spill index be before it is problematic?
Stain Index for Various Fluorochromes
Reagent
Clone
Filter
Stain Index
PE
RPA-T4
585/40
356.3
Alexa Fluor® 647
RPA-T4
660/20
313.1
APC
RPA-T4
660/20
279.2
PE-Cy7
RPA-T4
780/60
278.5
PE-Cy5
RPA-T4
695/40
222.1
PerCP-Cy5.5
Leu-3a
695/40
92.7
PE-Alexa Fluor® 610
RPA-T4
610/20
80.4
Alexa Fluor® 488
RPA-T4
530/30
75.4
FITC
RPA-T4
530/30
68.9
PerCP
Leu-3a
695/40
64.4
APC-Cy7
RPA-T4
780/60
42.2
Alexa Fluor® 700
RPA-T4
720/45
39.9
Pacific Blue™
RPA-T4
440/40
22.5
AmCyan
RPA-T4
525/50
20.2
Antibody Cocktail for Data Acquisition
•
•
•
•
•
•
•
•
CD4 FITC
CD127 PE
HLA-DR PerCP-Cy™5.5
CD45RA PE-Cy7
CD25 APC
CD8 APC-H7
CD3 V450
CD45 AmCyan
Schedule: Day 2
9:00–10:00
IV. Design and optimization of multicolor panels:
• Selection of fluorochromes
• Matching fluorochromes with antibody specificities
• Determining application-specific settings
Demonstration: Visualizing data on a virtual cytometer
10:00–12:00
Data analysis in BD FACSDiva software
12:00–1:00
Lunch
1:00–2:30
V. Controls and Data QC
Exercise 3: Finding and correcting a spillover problem
2:30–2:45
Break
2:45–4:00
Review and summary, discussion of participant issues
Multicolor Flow Cytometry Workshop:
IV. Panel Design & Application
Settings
Outline
3. Design your panel
•
•
•
•
Reserve the brightest fluorochromes for the dimmest
markers and vice versa
Avoid spillover from bright populations into detectors
requiring high sensitivity
Beware of tandem dye issues
Titrate antibodies for best separation
This allows you to:
•
•
Maintain resolution sensitivity where you need it most
Avoid artifacts of tandem dye degradation
Various Fluorochromes—Stain Index
Reagent
Clone
Filter
Stain Index
PE
RPA-T4
585/40
356.3
Alexa Fluor®647
RPA-T4
660/20
313.1
APC
RPA-T4
660/20
279.2
PE-Cy7
RPA-T4
780/60
278.5
PE-Cy5
RPA-T4
695/40
222.1
PerCP-Cy5.5
Leu-3a
695/40
92.7
PE-Alexa Fluor® 610
RPA-T4
610/20
80.4
Alexa Fluor® 488
RPA-T4
530/30
75.4
FITC
RPA-T4
530/30
68.9
PerCP
Leu-3a
695/40
64.4
APC-Cy7
RPA-T4
780/60
42.2
Alexa Fluor® 700
RPA-T4
720/45
39.9
Pacific Blue™
RPA-T4
440/40
22.5
AmCyan
RPA-T4
525/50
20.2
Spillover Affects Resolution Sensitivity
Without CD45 AmCyan
With CD45 AmCyan
CD19 FITC
Note that this is only an issue when the two markers (CD45
and CD19) are co-expressed on the same cell population.
Special Requirements for Tandem Dyes
Compensation requirements for tandem dye conjugates
can vary, even between two experiments with the same
antibody
• Degrade with exposure to light, temperature, and fixation
• Stained cells are most vulnerable
Solutions:
• Minimize exposure to above agents
• Use BD stabilizing fixative if a final fix is necessary
• Run label-specific compensation
False Positives Due to Tandem
Degradation
A. With CD8 APC-Cy7 and CD4 PE-Cy7:
Gating scheme
B. Without CD8 APC-Cy7:
CD8 APC-Cy7+ cells
CD4 PE-Cy7+ cells
False positives in
APC channel reduced
in absence of APC-Cy7
False positives
in PE channel
remain
New Tandems Can Be More Stable
APC-H7 as a replacement for APC-Cy7:
Comparison of Sample Stability
(in BD Stabilizing Fixative at RT)
250
% Spillover
200
CD4 APC-Cy7
150
CD8 APC-Cy7
CD4 APC-H7
100
CD8 APC-H7
50
0
0
1
2
4
6
8
Hours of light exposure
24
48
Antibody Titration Basics
For most purposes, the main objective is to maximize the
signal-to-noise ratio (pos/neg separation)
• This may occur at less than saturating antibody concentrations
• This may or may not be the manufacturer’s recommended titer,
depending on the application
Titer is affected by:
•
•
•
•
Staining volume (eg, 100 mL)
Number of cells (not critical up to ~5 x 106)
Staining time and temperature (eg, 30 min at RT)
Type of sample (whole blood, PBMCs, etc)
Antibody Titration Example
Outline
4. Optimize settings for your panel
•
•
Derive experiment-specific PMT settings
Run compensation controls for each experiment
This allows you to:
•
•
Use the most appropriate settings for your panel
Avoid gross errors of compensation
Application Settings for a New Panel (I)
Balancing detectors and checking spillover:
1. Start with the current baseline CS&T settings
2. Run single-stained BDTM CompBeads to see if all
populations are on scale
•
•
Decrease voltage if positives are off-scale
Increase voltage if the negative mean is below zero
3. Verify that each positive bead is at least 2x brighter in its
primary detector vs other detectors (use the unstained
control worksheet)
•
•
If not, increase voltage in the primary detector
Spill indexes for all combinations should be <0.8
Application Settings for a New Panel (II)
Optimizing voltages for cells of interest:
1. Run fully-stained cells and:
• Decrease voltages for any detectors where events are offscale
• Increase voltages for any detectors where low-end
resolution is poor (SDNEG PEAK should be 5–10x SDEN)
2. Save application settings
3. Run single-stained BD CompBeads and calculate
compensation
4. Run samples
Application Settings for an Existing Panel
1. Start with the current CS&T settings
2. Apply previously saved application settings
3. Run single-stained BD CompBeads and calculate
compensation
4. Run samples
Demonstration
Visualizing data using a virtual cytometer:
1. Demonstration of data display as PMT voltages
change
2. Note the percentage of variance due to
electronic noise at different voltages
Questions:
1. What percentage of the variance contributed by
electronic noise is acceptable?
2. Do you need to calculate this for all detectors
and all panels?
3. Is there such a thing as too high a voltage?
Multicolor Flow Cytometry Workshop:
V. Controls and Data QC
Outline
5. Run appropriate controls
•
•
•
Instrument setup controls (eg, voltage and compensation
determination)
Gating controls (eg, FMO)
Biological controls (eg, unstimulated samples, healthy
donors)
This allows you to:
•
•
•
Obtain consistent setup and compensation
Gate problem markers reproducibly
Make appropriate biological comparisons and conclusions
BD CompBeads as Single-Color Controls
BD CompBeads provide a
convenient way to create singlecolor compensation controls:
• Using the same antibodies as in
the experimental samples
• Creating a (usually) bright and
uniform positive fluorescent peak
• Without using additional cells
Frequent Compensation Questions
Do I need to use the same antibody for compensation as I
use in the experiment?
• Yes, for certain tandem dyes (eg, PE-Cy7, APC-Cy7)
Are capture beads better than cells for compensation?
• Usually, as long as the antibody binds to the bead and
is as bright or brighter than stained cells
Should compensation controls be treated the same as
experimental samples (eg, fixed and permeabilized)?
• Yes, although with optimal fix/perm protocols this may
not make much difference
Gating Controls
Isotype control: Non-specific antibody of same isotype as the
test antibody. For example :
• IgG1 FITC + IgG2a PE + IgG1 APC
Fluorescence-minus-one (FMO) control: All test antibodies
except the one of interest. For example :
• CD3 FITC + CD4 APC (no PE)
Combined control: All test antibodies except the one of interest,
which is replaced by an isotype control. For example :
• CD3 FITC + IgG2a PE + CD4 PE
Biological controls can sometimes be used as gating controls.
Gating Controls (continued)
• Isotype controls don’t take spillover into account
• FMO controls don’t take background staining into account
• Combined controls take both into account, but still may
not accurately represent the background staining of the
test antibody
Comparison of Gating Controls
Consider Using Lyophilized Reagents
• Lyophilization provides increased stability, even at room
temperature or 37°C
• One batch of reagents can be used for an entire
longitudinal study
• Pre-configured plates (BD Lyoplate™ plates) can avoid
errors of reagent addition
• Complex experiments (multiple stimuli, multiple
polychromatic staining cocktails) become easier
• Lyophilized cell controls can provide run-to-run
standardization
Outline
6. QC your data
•
•
•
Visually inspect compensation
Visually inspect gating
Set sample acceptance criteria
This allows you to:
•
Avoid classification errors and false conclusions due to
improper compensation and/or gating, or sample artifacts
Visually Inspect Compensation
• Create a template containing dot plots of each color
combination in your experiment, then examine a fully
stained sample for possible compensation problems
• Yikes!
Compensation Problems Can Have
Cascading Effects
Compensation at 110%
Compensation at 15%
Visually Inspect Gating
• Check gating across all samples in the experiment.
IFNg FITC
• Gates may need to be adjusted across donors and/or
experimental runs. Dynamic (eg, snap-to) gates may
help in some cases.
IL-2 PE
Types of Sample Acceptance Criteria
• Minimum viability and recovery for cryopreserved PBMCs
• Minimum number of events collected in an appropriate
gate (eg, lymphocytes)
• Minimum number of events within a region of interest, to
calculate an accurate percentage
Exercise 3
Finding and correcting a spillover problem:
1. Open the FCS file “exercise3.fcs”
2. Gate on small lymphcytes, then use the provided
worksheet to look at all color combinations
3. Using biexponential display, change compensation for
FITC - % AmCyan and note the changes in the plots
4. Find the compensation that aligns the FITC means of the
AmCyan positive and negative populations
Questions:
1. What could cause the discrepancy between calculated
compensation by AutoComp and visually appropriate
compensation on cells?
2. How might this problem, if uncorrected, affect your
results?
Outline: Review
1. Configure your instrument
2. Characterize your instrument
3. Design your panel
4. Optimize settings for your panel
5. Run appropriate controls
6. QC your data
A Question for You to Answer
How many colors can you combine and still have
robust results? This depends on:
-The experimental question
-The instrument used
-The markers to be combined
References
• Maecker HT, Frey T, Nomura, LE, Trotter J. Selecting fluorochrome
conjugates for maximum sensitivity. Cytometry A. 2004;62:169173.
• Maecker HT, Trotter J. Flow cytometry controls, instrument setup,
and the determination of positivity. Cytometry A. 2006;69:10371042.
• Roederer M. How many events is enough? Are you positive?
Cytometry A. 2008;73:384-385.
• McLaughlin BE, Baumgarth N, Bigos M, et al. Nine-color flow
cytometry for accurate measurement of T cell subsets and cytokine
responses. Part I: Panel design by an empiric approach.
Cytometry A. 2008;73:400-410.
Acknowledgements
•
•
•
•
•
•
•
Laurel Nomura
Margaret Inokuma
Maria Suni
Maria Jaimes, M.D.
Smita Ghanekar, Ph.D.
Jack Dunne, Ph.D.
Skip Maino, Ph.D.
• Joe Trotter, Ph.D.
• Dennis Sasaki
• Marina Gever