 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

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
► cell-based expression systems for recombinant proteins
► purification from natural sources
► production in vitro by cell-free translation systems
► synthetic methods for peptides
►
Common physical supports include glass slides, silicon, microwells, nitrocellulose or PVDF membranes, microbeads
► 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
► 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

Mass Sorting (filtering) Ionization
Ion
Source
Form ions
(charged molecules)
Mass Analyzer
Sort Ions by Mass (m/z)
Detection
Ion
Detector
Detect ions
Inlet • Solid
• Liquid
•
Vapor
100
75
50
25
0
1330 1340 1350
Mass Spectrum

Pressure = 1 atm
Inner tube diam. = 100 um
N
2
Sample in solution
N
2 gas
High voltage applied to metal sheath (~4 kV)
Sample Inlet Nozzle
(Lower Voltage)
Partial vacuum
++
+
+ +
+
+
+ +
+ +
+
+
+
+
+ +
+
+
++
+
++
+ +
+
++
+
+
+
+ +
+
+
+
+
+
MH +
MH
2
+
MH
3
+
Charged droplets
All compounds must be ionized, but ionization efficiency is variable with different compounds

2D Gel Electrophoresis  Mass Spectrometry
Source: UNC Proteomics Core Facility

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 p ij of observing each peptide j from protein i. APEX involves training a classifier to estimate O i
, the prior estimate of the number of unique peptides expected from a given protein during such an experiment. By correcting for O i
, 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
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
m
pooled RNA from liver (~50% w/w), kidneys, lungs, brain, thymus, testes, spleen, heart, and muscle of untreated Wistar rats
32 genes were found to be significantly upregulated and 17 were repressed following bromobenzene treatment
63 genes were found to be significantly upregulated and 35 genes were repressed following bromobenzene treatment
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.

Dettmer et al., MS Reviews, 26 , 51, 2007

CH
2
OP
3-phosphoglyceric
CHOH acid dehydrogenase
CH
2
O-
CH
2
OP
CO
CH
2
O-

Douglas B. Kell, Curr Opin Microbiol. 7 , 296, 2004

NMR
LC/UV
GC/MS
LC/MS m
M (10 -6 ) nM (10 -9 ) pM (1012 ) fM (1015 )
Adapted from Sumner, LW, et al., Phytochem, 62, 817,2003

Off-line hyphenation
MS
NMR
LC/MS
GC/MS
CE/MS
LC/NMR
Chromatography

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

• 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

•
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.

(Hydrogen nuclei act like little magnets)
Hydrogen nuclei out and about Hydrogen nuclei in a magnetic field

RF pulse detector
Aligned with the big magnetic field
Excited state transverse to the field
Precession based on magnetic environment
& detection

PROS
• High structural information content
• Very high intra/inter-lab reproducibility
•
Inherently quantitative
(no need for authentic standards)
• Minimal sample processing required
• Non-destructive
CONS
• Expensive instrumentation
• Relatively low sensitivity (typically
> m
M concentrations required)
• Spectral crowding can hinder interpretation
• Long chain aliphatics are challenging (e.g. fatty acids)

Adapted from D. Robertson, Pfizer Global Research and Development

“Biomarker Windows”
Nature Reviews: Drug Discovery Nicholson et al. (2002)

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

15
PC2
10
5
0
-5
-10
-15
-40
ANIT
-30 -20
Control
-10 0
PC1
10
25
20
PC2
15
10
5
0
-5
-10
-15
-20
-25
-30
ANIT
-20
PAP
-10
Control
0
PC1
10 p -Aminophenol (PAP) a
-naphthylisothiocyanite (ANIT)
Control
Adapted from D. Robertson, Pfizer Global Research and Development

Set of 1D
1 H spectra
KEGG
Analysis
NMR
Database
Metabolite
ID
1 H & 13 C
Prediction
2D spectra
1 H & 13 C

http://www.metabolomics.ca/

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.

Vehicle
Methapyrilene-induced liver injury in the rat
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.