Arivusudar Marimuthu

Human Protein Reference Database—2009 update

Human Protein Reference Database (HPRD—http://www.hprd.org/), initially described in 2003, is a database of curated proteomic information pertaining to human proteins. We have recently added a number of new features in HPRD. These include PhosphoMotif Finder, which allows users to find the presence of over 320 experimentally verified phosphorylation motifs in proteins of interest. Another new feature is a protein distributed annotation system—Human Proteinpedia (http://www.humanproteinpedia.org/)—through which laboratories can submit their data, which is mapped onto protein entries in HPRD. Over 75 laboratories involved in proteomics research have already participated in this effort by submitting data for over 15 000 human proteins. The submitted data includes mass spectrometry and protein microarray-derived data, among other data types. Finally, HPRD is also linked to a compendium of human signaling pathways developed by our group, NetPath (http://www.netpath.org/), which currently contains annotations for several cancer and immune signaling pathways. Since the last update, more than 5500 new protein sequences have been added, making HPRD a comprehensive resource for studying the human proteome.

A draft map of the human proteome

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

A Compendium of Potential Biomarkers of Pancreatic Cancer

Akhilesh Pandey and colleagues describe a compendium of potential biomarkers that can be systematically validated by the pancreatic cancer community.

Plasma Proteome Database as a resource for proteomics research: 2014 update.

Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization’s (HUPO’s) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10 546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.

Comparisons of tyrosine phosphorylated proteins in cells expressing lung cancer-specific alleles of EGFR and KRAS.

We have used unbiased phosphoproteomic approaches, based on quantitative mass spectrometry using stable isotope labeling with amino acids in cell culture (SILAC), to identify tyrosine phosphorylated proteins in isogenic human bronchial epithelial cells (HBECs) and human lung adenocarcinoma cell lines, expressing either of the two mutant alleles of EGFR (L858R and Del E746-A750), or a mutant KRAS allele, which are common in human lung adenocarcinomas. Tyrosine phosphorylation of signaling molecules was greater in HBECs expressing the mutant EGFRs than in cells expressing WT EGFR or mutant KRAS. Receptor tyrosine kinases (such as EGFR, ERBB2, MET, and IGF1R), and Mig-6, an inhibitor of EGFR signaling, were more phosphorylated in HBECs expressing mutant EGFR than in cells expressing WT EGFR or mutant RAS. Phosphorylation of some proteins differed in the two EGFR mutant-expressing cells; for example, some cell junction proteins (β-catenin, plakoglobin, and E-cadherin) were more phosphorylated in HBECs expressing L858R EGFR than in cells expressing Del EGFR. There were also differences in degree of phosphorylation at individual tyrosine sites within a protein; for example, a previously uncharacterized phosphorylation site in the nucleotide-binding loop of the kinase domains of EGFR (Y727), ERBB2 (Y735), or ERBB4 (Y733), is phosphorylated significantly more in HBECs expressing the deletion mutant than in cells expressing the wild type or L858R EGFR. Signaling molecules not previously implicated in ERBB signaling, such as polymerase transcript release factor (PTRF), were also phosphorylated in cells expressing mutant EGFR. Bayesian network analysis of these and other datasets revealed that PTRF might be a potentially important component of the ERBB signaling network.

A comprehensive map of the human urinary proteome.

The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.

Proteogenomic Analysis of Mycobacterium tuberculosis By High Resolution Mass Spectrometry

The genome sequencing of H37Rv strain of Mycobacterium tuberculosis was completed in 1998 followed by the whole genome sequencing of a clinical isolate, CDC1551 in 2002. Since then, the genomic sequences of a number of other strains have become available making it one of the better studied pathogenic bacterial species at the genomic level. However, annotation of its genome remains challenging because of high GC content and dissimilarity to other model prokaryotes. To this end, we carried out an in-depth proteogenomic analysis of the M. tuberculosis H37Rv strain using Fourier transform mass spectrometry with high resolution at both MS and tandem MS levels. In all, we identified 3176 proteins from Mycobacterium tuberculosis representing ∼80% of its total predicted gene count. In addition to protein database search, we carried out a genome database search, which led to identification of ∼250 novel peptides. Based on these novel genome search-specific peptides, we discovered 41 novel protein coding genes in the H37Rv genome. Using peptide evidence and alternative gene prediction tools, we also corrected 79 gene models. Finally, mass spectrometric data from N terminus-derived peptides confirmed 727 existing annotations for translational start sites while correcting those for 33 proteins. We report creation of a high confidence set of protein coding regions in Mycobacterium tuberculosis genome obtained by high resolution tandem mass-spectrometry at both precursor and fragment detection steps for the first time. This proteogenomic approach should be generally applicable to other organisms whose genomes have already been sequenced for obtaining a more accurate catalogue of protein-coding genes.

Genomewide mRNA profiling of esophageal squamous cell carcinoma for identification of cancer biomarkers

Esophageal squamous cell carcinoma (ESCC) is a common cancer worldwide that has a poor survival rate among patients mainly because of lack of early markers to identify this cancer. Molecular mechanisms contributing to initiation and progression of esophageal squamous cell carcinoma are still poorly understood. Development of DNA microarrays technology allows high-throughput identification of gene expression profiles in cancers. In order to identify molecules as candidates for early diagnosis and/or therapeutic targets, we analyzed mRNA expression profiles of 20 surgically resected specimens of ESCC and compared them to their adjacent normal epithelium using whole genome DNA microarrays. We observed 119 genes significantly upregulated in ESCC samples as compared to the adjacent normal epithelium. The expression of two previously unreported overexpressed genes, ORAOV2 and FAP, was validated at the protein level by immunohistochemical labeling of tissue microarrays (TMAs) and archival tissue sections. Overexpression of ORAOV2 was observed in 116/118 (98%) of ESCC cases, while FAP overexpression was in 79/116 (68%) of cases. Osteopontin, which was identified in earlier studies, was observed to be upregulated in 114/118 (97%) cases. Overall, using this approach, we have identified a number of promising novel candidates that can be validated further for their potential to serve as biomarkers for ESCC.

Differential proteomic analysis of synovial fluid from rheumatoid arthritis and osteoarthritis patients

BackgroundRheumatoid arthritis and osteoarthritis are two common musculoskeletal disorders that affect the joints. Despite high prevalence rates, etiological factors involved in these disorders remain largely unknown. Dissecting the molecular aspects of these disorders will significantly contribute to improving their diagnosis and clinical management. In order to identify proteins that are differentially expressed between these two conditions, a quantitative proteomic profiling of synovial fluid obtained from rheumatoid arthritis and osteoarthritis patients was carried out by using iTRAQ labeling followed by high resolution mass spectrometry analysis.ResultsWe have identified 575 proteins out of which 135 proteins were found to be differentially expressed by ≥3-fold in the synovial fluid of rheumatoid arthritis and osteoarthritis patients. Proteins not previously reported to be associated with rheumatoid arthritis including, coronin-1A (CORO1A), fibrinogen like-2 (FGL2), and macrophage capping protein (CAPG) were found to be upregulated in rheumatoid arthritis. Proteins such as CD5 molecule-like protein (CD5L), soluble scavenger receptor cysteine-rich domain-containing protein (SSC5D), and TTK protein kinase (TTK) were found to be upregulated in the synovial fluid of osteoarthritis patients. We confirmed the upregulation of CAPG in rheumatoid arthritis synovial fluid by multiple reaction monitoring assay as well as by Western blot. Pathway analysis of differentially expressed proteins revealed a significant enrichment of genes involved in glycolytic pathway in rheumatoid arthritis.ConclusionsWe report here the largest identification of proteins from the synovial fluid of rheumatoid arthritis and osteoarthritis patients using a quantitative proteomics approach. The novel proteins identified from our study needs to be explored further for their role in the disease pathogenesis of rheumatoid arthritis and osteoarthritis.Sartaj Ahmad and Raja Sekhar Nirujogi contributed equally to this article.

Quantitative tissue proteomics of esophageal squamous cell carcinoma for novel biomarker discovery

Esophageal squamous cell carcinoma (ESCC) is among the top ten most frequent malignancies worldwide. In this study, our objective was to identify potential biomarkers for ESCC through a quantitative proteomic approach using the isobaric tags for relative and absolute quantitation (iTRAQ) approach. We compared the protein expression profiles of ESCC tumor tissues with the corresponding adjacent normal tissue from ten patients. LC-MS/MS analysis of strong cation exchange chromatography fractions was carried out on an Accurate Mass QTOF mass spectrometer, which led to the identification of 687 proteins. In all, 257 proteins were identified as differentially expressed in ESCC as compared to normal. We found several previously known protein biomarkers to be upregulated in ESCC including thrombospondin 1 (THBS1), periostin 1 (POSTN) and heat shock 70 kDa protein 9 (HSPA9) confirming the validity of our approach. In addition, several novel proteins that had not been reported previously were identified in our screen. These novel biomarker candidates included prosaposin (PSAP), plectin 1 (PLEC1) and protein disulfide isomerase A 4 (PDIA4) that were further validated to be overexpressed by immunohistochemical labeling using tissue microarrays. The success of our study shows that this mass spectrometric strategy can be applied to cancers in general to develop a panel of candidate biomarkers, which can then be validated by other techniques.