Transcript Toxicants and Proteins: Proteomics

Application of omics technologies
in toxicology:
Proteomics and Metabolomics
Most Commonly Used Proteomics Techniques:
 Antibody arrays
 Protein activity arrays
 2-D gels
 “Shotgun” proteomics
 ICAT technology
 SELDI
100% protein sequence coverage: a modern form of surrealism in proteomics. Meyer et al Amino Acids. 2010 Jul 13.
Antibody Arrays
• Screening protein-protein interactions
• Studying protein posttranslational modifications
• Examining protein expression patterns
Antibody Arrays
The layout design of the BD Clontech™ Ab Microarray 380. The BD
Clontech™ Ab Microarray 380 (#K1847-1) contains 378 monoclonal antibodies
arrayed in a 32 x 24 grid. Each antibody is printed in duplicate. Dark gray dots
at the corners represent Cy3/Cy5-labeled bovine serum albumin (BSA) spots,
which serve as orientation markers. The open circles correspond to unlabeled
BSA spots, which serve as negative controls. For complete descriptions of the
proteins profiled by the Ab Microarray 380, visit bdbiosciences.com
Limitations, Challenges and Bottlenecks
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Protein production:
►cell-based expression systems for recombinant proteins
► purification from natural sources
► production in vitro by cell-free translation systems
► synthetic methods for peptides
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Immobilization surfaces and array formats:
► Common physical supports include glass slides, silicon,
microwells, nitrocellulose or PVDF membranes, microbeads
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Protein immobilization should be:
► reproducible
► applicable to proteins of different properties (size, charge, …)
► amenable to high throughput and automation, and compatible
with retention of fully functional protein activity
► such that maintains correct protein orientation
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Array fabrication:
► robotic contact printing
► ink-jetting
► piezoelectric spotting
► photolithography
Protein Activity Arrays
Panomics® Transcription Factor Arrays:
A set of biotin-labeled DNA binding
oligonucleotides (TranSignal™ probe mix)
is preincubated with any nuclear extract of
interest to allow the formation of
protein/DNA (or TF/DNA) complexes;
The protein/DNA complexes are separated
from the free probes;
The probes in the complexes are then
extracted and hybridized to the
TranSignal™ Array. Signals can be detected
using either x-ray film or chemi-luminescent
imaging. All reagents for HRP-based
chemiluminescent detection are included.
Source: Panomics, Inc.
Protein Activity Arrays
Gel Shift Assay
Protein Array
Source: Panomics, Inc.
2D Gel Electrophoresis + Mass Spectrometry
Meyer et al Amino Acids. 2010 Jul 13.
2D Gel Electrophoresis  Protein Resolution
Bandara & Kennedy (2002)
2D Gel Electrophoresis  Image Analysis
Courtesy of Decodon
Courtesy of Alphainnotech
Acquiring a Mass Spectrum
Ionization
Mass Sorting (filtering)
Ion
Source
Detection
Ion
Detector
Mass Analyzer
Form ions
(charged molecules)
Sort Ions by Mass (m/z)
Detect ions
100
75
Inlet
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Solid
Liquid
Vapor
50
25
0
1330
1340
1350
Mass Spectrum
Ion Sources make ions from sample molecules
Electrospray ionization:
Pressure = 1 atm
Inner tube diam. = 100 um
Partial
vacuum
Sample Inlet Nozzle
(Lower Voltage)
MH+
N2
Sample in solution
N2 gas
+
+ ++
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+ ++
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+ +
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+
MH2+
+
MH3+
High voltage applied
to metal sheath (~4 kV)
Charged droplets
All compounds must be ionized, but ionization efficiency is variable with different compounds
Typical MS Spectra
2D Gel ElectrophoresisMass Spectrometry
Source: UNC Proteomics Core Facility
Image courtesy of University of Arizona Proteomics Core
SEQUEST is a program that uses raw peptide MS/MS data (off TSQ-7000 or LCQ) to identify
unknown proteins. It works by searching protein and nucleotide databases (in FASTA format) on
the web for peptides that match the molecular weight of the unknown peptides produced by
digestion of your protein(s) of interest. Theoretical MS/MS spectra are then generated and a
score is given to each one. The top 500 scored theoretical peptides are retained and a cross
correlation analysis is then performed between the un-interpreted MS/MS spectra (real MS/MS
spectra) of unknown peptides with each of the retained theoretical MS/MS spectra. Highly
correlated spectra result in identification of the peptide sequences and multiple peptide
identification and thus determine the protein and organism of origin corresponding to the
unknown protein sample.
SHOTGUN PROTEOMICS
Proteins are analyzed by standard shotgun proteomics, beginning with tryptic digest of a protein mixture, liquid chromatographic separation of the
mixture (2D HPLC), analysis of peptide masses by mass spectrometry (MS) and fragmentation of peptides and subsequent analysis of the
fragmentation spectra (MS/MS). Each step introduces bias into the peptides ultimately interpreted from the analysis, thereby affecting the
probability pij of observing each peptide j from protein i. APEX involves training a classifier to estimate Oi, the prior estimate of the number of unique
peptides expected from a given protein during such an experiment. By correcting for Oi, the number of peptides observed per protein thereby
provides an estimate of the protein's abundance. HPLC, high-performance liquid chromatography. Nature Biotechnology 25, 117 - 124 (2007)
Limitations, Challenges and Bottlenecks
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Resolution:
► number of proteins that can be separated/distinguished (500,000?!?)
► pI resolution
► mass resolution (gels and mass spectrometry)
Amount of the protein in the sample:
► too little to be seen on a 2D gel?
► too little to be extracted and digested?
Protein solubility
Database searching and peptide identification
Bandara & Kennedy (2002)
Schneider LV, Hall MP. Drug Discov Today. 2005 10:353-63.
Two-dimensional electrophoretic analysis of rat liver total proteins. The proteins were separated on a pH 3–10
nonlinear IPG strip (left), or pH 4-7 IPG strip (right), followed by a 10% SDS–polyacrylamide gel. The gel was
stained with Coomassie blue. The spots were analyzed by MALDI-MS. The proteins identified are designated
with the accession numbers of the corresponding database.
From Fountoulakis & Suter (2002)
Summary of the 2-D gel electrophoresis data
• In total, 273 different gene products were identified from all gels:
65 gene products were only detected in the gels carrying total
52 in the gels carrying cytosolic
remaining proteins were found in both samples
• 45 proteins out of the 62 found in the gels carrying total protein samples
were detected in the broad pH range 3–10 gel, 11 in the narrow pH range
and nine in both types of gels
• 52 proteins only detected in the gels carrying the cytosolic fraction, except
for 6 which were found in the broad pH range 3–10 gel, were found in one
of the narrow pH range gels only (narrow pH range strips helped to detect
46 proteins not found in the broad range gels)
• Protein distribution was based on the protein identification by mass
spectrometry and may not be complete due to:
spot loss during automatic excision
peptide loss mainly from weak spots
spot overlapping
small protein size
• About 5000 spots were excised from 13 2-D gels, 5 carrying total and 8
carrying cytosolic proteins. The analysis resulted in the identification of
about 3000 proteins, which were the products of 273 different genes
From Fountoulakis & Suter (2002)
Summary of the 2-D gel electrophoresis data
From Fountoulakis & Suter (2002)
Animals:
Male Wistar rats
(10–12 weeks, bw: 225±8 g)
Treatment:
Bromobenzene
(i.p., 5.0 mmol/kg bw)
dissolved in corn oil (40% v/v)
Duration of treatment:
24 hrs
The bromobenzene dose was hepatotoxic, and this was confirmed by the finding of
a nearly complete glutathione depletion at 24 hr after bromobenzene administration.
The low level of oxidised (GSSG) relative to reduced glutathione (GSH) indicates
that the depletion is primarily due to conjugation and to a much lesser extent due to
oxidation of glutathione. The bromobenzene administration resulted in on average
7% decrease in body weight after 24 hr.
From: Heijne et al. (2003)
Gene Expression Profiling
• Liver samples, total RNA (50 mg/array experiment)
• cDNA microarrays (3000 genes)
• Reference sample:
pooled RNA from liver (~50% w/w), kidneys, lungs, brain, thymus, testes,
spleen, heart, and muscle of untreated Wistar rats
• Duplicated microarray/sample
• 2-Fold cutoff (p<0.01) relative to the vehicle control:
32 genes were found to be significantly upregulated and 17 were
repressed following bromobenzene treatment
• 1.5-Fold cutoff (p<0.01) relative to the vehicle control:
63 genes were found to be significantly upregulated and 35 genes were
repressed following bromobenzene treatment
• Functional groups:
Drug metabolism
Glutathione metabolism
Oxidative stress
Acute phase response
Protein synthesis
Protein degradation
Others
From: Heijne et al. (2003)
Glutathione metabolism:
Oxidative stress:
From: Heijne et al. (2003)
Protein Expression Profiling
• 3 two-dimensional gels were
prepared from each sample
• A reference protein pattern
contained 1124 protein spots
• 24 proteins were differentially
expressed (BB or Corn oil)
From: Heijne et al. (2003)
Liver is unique in its capability to regenerate after an injury. Liver
regeneration after a 2/3 partial hepatectomy served as a classical model
and is adopted frequently to study the mechanism of liver regeneration. In
the present study, semi-quantitative analysis of protein expression in
mouse liver regeneration following partial hepatectomy was performed
using an iTRAQ technique. Proteins from pre-PHx control livers and livers
regenerating for 24, 48 and 72 h were extracted and inspected using 4-plex
isotope labeling, followed by liquid chromatography fractionation, mass
spectrometry and statistical differential analysis. A total of 827 proteins
were identified in this study. There were 270 proteins for which
quantitative information was available at all the time points in both
biologically duplicate experiments. Among the 270 proteins, Car3, Mif,
Adh1, Lactb2, Fabp5, Es31, Acaa1b and LOC100044783 were consistently
down-regulated, and Mat1a, Dnpep, Pabpc1, Apoa4, Oat, Hpx, Hp and Mt1
were up-regulated by a factor of at least 1.5 from that of the controls at one
time point or more. The regulation of each differential protein was also
demonstrated by monitoring its time-dependent expression changes
during the regenerating process. We believe this is the first report to
profile the protein changes in liver regeneration utilizing the iTRAQ
proteomic technique.
Metabolomics is the Most Closely
Related to Phenotype
Dettmer et al., MS Reviews, 26, 51, 2007
Studying the Whole Metabolome
Focused analysis of a single metabolic pathway
CH2OP
CH2OP
3-phosphoglyceric
CHOH
CH2O-
acid dehydrogenase
CO
CH2O-
Unbiased analysis of the entire metabolome
Some Definitions
Typical Size Range of Metabolites
Douglas B. Kell, Curr Opin Microbiol. 7, 296, 2004
Range of Tools Required to Cover the Entire Metabolome
NMR
mM (10-6)
LC/UV
nM (10-9)
GC/MS
pM (10-12)
LC/MS
fM (10-15)
Adapted from Sumner, LW, et al., Phytochem, 62, 817,2003
Main Analytical Approaches to Metabolomics
Off-line
hyphenation
MS
LC/MS
GC/MS
NMR
CE/MS
Chromatography
LC/NMR
Comparison of NMR vs MS for Metabonomics
Analytical Considerations
NMR
MS
Sensitivity
Reproducibility – w/in lab
Reproducibility – across labs
Quantitation
Sample Prep Requirements
Sample Analysis Automation
Versatility
Selectivity
Non-selectivity
Taken from D.G. Robertson, Toxicological Sciences, 85, 809, 2005
Features of GC/MS Metabolomics
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Useful for volatiles or compounds that can be derivatized to volatile
compounds (derivatization often required)
Ideal for long chain compounds e.g. FFA, acyl carnitines, etc
More stable and reproducible than LC/MS
Most advanced metabolomics libraries
Standards are typically required for positive identification
Inexpensive technology
Experiment
Library match
Features of LC/MS Metabolomics
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Chromatography can be tailored to specific chemical classes
Various MS analyzers can be coupled e.g. triple quad, TOF, ion trap each with it’s
own advantages in speed, resolution and sensitivity.
Very high mass accuracy available with TOF instruments (< 2ppm)
Variable ionization efficiencies and matrix suppression leads to poor quantitation
w/out standards
Excellent for targetted metabolomics, more challenging for global “unbiased” profiling
Q-TOF can acquire high res data + MS/MS for fragmentation analyses
Libraries are available but suffer from inconsistent retention times in the LC front end.
The NMR Phenomenon
(Hydrogen nuclei act like little magnets)
Hydrogen nuclei out and about
Hydrogen nuclei in a magnetic field
The NMR Experiment
RF
detector
pulse
Aligned with the big
magnetic field
Excited state
transverse to the field
Precession
based on magnetic
environment
& detection
The Chemical Shift
Different hydrogen atoms (gray) are in unique
chemical and magnetic environments
This results in different precession frequencies and
distinct spectral features.
PROS
Features of NMR
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High structural information content
Very high intra/inter-lab
reproducibility
Inherently quantitative
(no need for authentic standards)
Minimal sample processing
required
Non-destructive
CONS
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Expensive instrumentation
Relatively low sensitivity (typically
>mM concentrations required)
Spectral crowding can hinder
interpretation
Long chain aliphatics are
challenging (e.g. fatty acids)
Normal Metabolic Profiles (rat urine)
Day 5
Day 4
Day 3
Day 2
Day 1
Adapted from D. Robertson, Pfizer Global Research and Development
Functional NMR Spectrum of Rat Urine
“Biomarker Windows”
Nature Reviews: Drug Discovery Nicholson et al. (2002)
Quantitative Fitting with NMR Database
Data Analysis in Metabolomics
NMR Spectra
Primary Data
Processing
Unsupervised mapping
of data in 3D space
Supervised classification
and calculation of
confidence intervals
Nature Reviews: Drug Discovery Nicholson et al. (2002)
Adapted from D. Robertson, Pfizer Global Research and Development
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PC2
PC2
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ANIT
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ANIT
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Control
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PC1
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0
PAP
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PC1
-40
Control
-15
10
-25
-30
-20
-10
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10
p-Aminophenol (PAP)
a-naphthylisothiocyanite (ANIT)
Control
Adapted from D. Robertson, Pfizer Global Research and Development
Tools to Identify Biomarkers
Set of 1D
1H spectra
NMR
Database
KEGG
Analysis
Metabolite
ID
1H
& 13C
Prediction
2D spectra
1H & 13C
The Human Metabolome Database
http://www.metabolomics.ca/
Mapping to Pathway Databases
Proteome Res., 5 (7), 1586 -1601, 2006
Systems Toxicology: Integrated Genomic, Proteomic and Metabonomic
Analysis of Methapyrilene Induced Hepatotoxicity in the Rat
Andrew Craig, James Sidaway, Elaine Holmes, Terry Orton, David Jackson, Rachel Rowlinson, Janice Nickson, Robert Tonge, Ian Wilson, and Jeremy
Nicholson
Abstract:
Administration of high doses of the histamine antagonist methapyrilene to rats causes periportal liver necrosis. The
mechanism of toxicity is ill-defined and here we have utilized an integrated systems approach to understanding the toxic
mechanisms by combining proteomics, metabonomics by 1H NMR spectroscopy and genomics by microarray gene
expression profiling. Male rats were dosed with methapyrilene for 3 days at 150 mg/kg/day, which was sufficient
to induce liver necrosis, or a subtoxic dose of 50 mg/kg/day. Urine was collected over 24 h each day, while blood
and liver tissues were obtained at 2 h after the final dose. The resulting data further define the changes that occur
in signal transduction and metabolic pathways during methapyrilene hepatotoxicity, revealing modification of
expression levels of genes and proteins associated with oxidative stress and a change in energy usage that is reflected in
both gene/protein expression patterns and metabolites. The difficulties of combining and interpreting multi-omic
data are considered.
Methapyrilene-induced liver injury in the rat
Vehicle
10 mg/kg, 7 days
100 mg/kg, 7 days
100 mg/kg, 7 days
Hamadeh et al 2002 Tox Path
“Systems Toxicology: Integrated Genomic, Proteomic and Metabonomic Analysis of Methapyrilene Induced
Hepatotoxicity in the Rat”
Proteins altered and identified between control and
methapyrilene dosed groups. Proteins are numbered
Ex where elevated and Rx where reduced.
Average standard 1H NMR spectra of liver from each treatment group.
This figure shows clearly dose related elevations
and composition changes in fatty acid species…
“Systems Toxicology: Integrated Genomic, Proteomic and Metabonomic Analysis of Methapyrilene Induced
Hepatotoxicity in the Rat”
“Systems Toxicology: Integrated Genomic, Proteomic and Metabonomic Analysis of Methapyrilene Induced
Hepatotoxicity in the Rat”
• Our aim was to determine the impact of drug toxicity on hepatic metabolic pathways and also ascertain whether a
multiomic systems biology approach would result in improved understanding of the mechanism of hepatotoxicity of the
drug
• The combination of information from gene, protein and metabolite levels provides an integrated picture of the response
to methapyrilene-induced hepatotoxicity with mutually supporting and mutually validating evidence arising from each
biomolecular level. As expected there were several instances where genes and proteins, either encoded by the same
gene or by other genes within the same pathway, were both co regulated by methapyrilene toxicity, and sometimes this
was in concert with an associated metabolic product
However:
Strategy of parallel omic data sets: It should be noted that alterations in expression of genes or enzyme levels and
modification of protein forms, while suggesting a potential target of toxic effects, do not imply that function or activity
must be altered… Alterations to metabolic profiles reflect function and so may serve to aid interpretation of corresponding
gene expression and proteomic analyses… Furthermore, as metabolites unlike genes do not suffer the problem of
orthology, observed metabolic effects are likely to be highly conserved between species and integrated systems
approaches applied to two species may be one framework within which to reconcile and understand the similarities and
differences in genetic wiring of common biological processes between different species.
Issue of experimental design: …looking at time points where toxicity is already well developed mitigates against
obtaining a clear understanding of the temporal dynamics of the mechanism, especially as changes at the gene, protein
and metabolite level may proceed at different rates and on different time scales. As such we might expect highly non
linear relationships between the concentrations of various species at the different levels of biomolecular organization…
Issue of molecular resolution: …we detected 100s of gene expression changes compared to the relatively small number
of changes detected by the other two technologies. It may thus be likely that insufficient detail was obtained at each
biomolecular level to elaborate fully on mechanism of methapyrilene toxicity…
Statistical difficulties: Since each data type usually requires tailored preprocessing (normalization, transformation,
scaling, etc.) combining multiple data sets presents a significant analytical challenge. Here, we have performed a separate
analysis at the gene, protein, and metabolite level and integrated the knowledge gained from each data set to uncover
pathways which responded to the methapyrilene-induced toxicity.