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Proteomics Proteomics

Proteomics - unc.edu 2009.pdf · Areas of Application for Proteomics Most Commonly Used Proteomics Techniques: Antibody arrays Protein activity arrays 2-D gels ... 2D Gel Electrophoresis

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ProteomicsProteomics

Areas of Application for Proteomics

Most Commonly Used Proteomics Techniques:

Antibody arrays

Protein activity arrays

2-D gels

ICAT technology

SELDI

Limitations:

protein sources

surfaces and formats

protein immobilization

fabrication

Examples

Areas of Application for Proteomics

• Diagnostics:►detection of antigens and antibodies in blood samples► profiling of sera to discover new disease markers► environment and food monitoring

• Protein expression profiling:► organ and disease specific arrays

• Library screening:► isolation of individual members from display libraries for

further expression or manipulation► selection of antibodies and protein scaffolds from phage

or ribosome display libraries for use in capture arrays• Protein functional analysis:

► ligand-binding properties of receptors► enzyme activities► protein-protein interactions► antibody cross reactivity and specificity, epitope mapping

• Screening protein-protein interactions • Studying protein posttranslational modifications• Examining protein expression patterns

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

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.

Protein Activity Arrays

Source: Panomics, Inc.

Protein Activity Arrays

Gel Shift Assay Protein Array

Source: Panomics, Inc.

Limitations, Challenges and Bottlenecks

• 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

• Immobilization surfaces and array formats:► Common physical supports include glass slides, silicon, microwells, nitrocellulose or PVDF membranes, microbeads

• 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

• Array fabrication:► robotic contact printing► ink-jetting► piezoelectric spotting► photolithography

2D Gel Electrophoresis + Mass Spectrometry

2D Gel Electrophoresis Protein Resolution

Bandara & Kennedy (2002)

2D Gel Electrophoresis Protein Resolution

Courtesy of Bio-Rad

Courtesy of Bio-Rad

Courtesy of Fermentas

2D Gel Electrophoresis Image Analysis

Courtesy of Decodon

Courtesy of Alphainnotech

Bandara & Kennedy (2002)

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.

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Bandara & Kennedy (2002)

Isotope Coded Affinity Tag (ICAT) Analysis

Perticoin et al., Toxicologic Pathology, 32(Suppl. 1):122–130, 2004

SELDI Analysis

From: www.evms.edu/vpc/seldi/seldiprocess/

Representative “raw” spectra and “gel-view” (grey-scale) of serum from a normal donor, and from patients with either BPH (benign prostate hyperplasia) or prostate cancer (PCA) using the IMAC3-Cu chip chemistry

The upregulated 11.9 kDa biomarker from the TMPD-treated rats was searched via Tagldent (SWISS-PROT), yielding a tentative identity as parvalbumin-alpha. This candidate was subsequently purified, peptide mapped and searched to confirm the identity. Parvalbumin is involved in muscle homeostasis.

Courtesy CIPHERGEN®

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)

Two-dimensional electrophoretic analysis of rat liver cytosolic proteins. The proteins were separated on a pH 3–10 nonlinear IPG strip (left), or pH 5–6 IPG strip (right), followed by a 10% SDS–polyacrylamide gel. The spots were analyzed by MALDI-MS. The proteins identified are designated with the accession numbers of the corresponding database.

From Fountoulakis & Suter (2002)

• In total, 273 different gene products were identified from all gels:65 gene products were only detected in the gels carrying total52 in the gels carrying cytosolicremaining 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 excisionpeptide loss mainly from weak spotsspot overlappingsmall 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

Summary of the 2-D gel electrophoresis data

From Fountoulakis & Suter (2002)

From Fountoulakis & Suter (2002)

Summary of the 2-D gel electrophoresis data

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)

• Liver samples, total RNA (50 μg/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 metabolismGlutathione metabolismOxidative stressAcute phase responseProtein synthesisProtein degradationOthers

Gene Expression Profiling

From: Heijne et al. (2003)

Glutathione metabolism:

Oxidative stress:

From: Heijne et al. (2003)

Acute phase response:

From: Heijne et al. (2003)

From: Heijne et al. (2003)

• 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)

Protein Expression Profiling

Proteome Res., 5 (7), 1586 -1601, 2006

Systems Toxicology: Integrated Genomic, Proteomic and MetabonomicAnalysis 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-omicdata are considered.

Vehicle 10 mg/kg, 7 days

100 mg/kg, 7 days100 mg/kg, 7 days

Methapyrilene-induced liver injury in the rat

Hamadeh et al 2002 Tox Path

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 elevationsand 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”

“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.