Kumaran Kandasamy

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.

The BioPAX community standard for pathway data sharing

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.

NetPath: a public resource of curated signal transduction pathways.

We have developed NetPath as a resource of curated human signaling pathways. As an initial step, NetPath provides detailed maps of a number of immune signaling pathways, which include approximately 1,600 reactions annotated from the literature and more than 2,800 instances of transcriptionally regulated genes - all linked to over 5,500 published articles. We anticipate NetPath to become a consolidated resource for human signaling pathways that should enable systems biology approaches.

Human Protein Reference Database and Human Proteinpedia as Discovery Tools for Systems Biology

Although high-throughput technologies used in biology have resulted in the accumulation of vast amounts of data in the literature, it is becoming difficult for individual investigators to directly benefit from this data because they are not easily accessible. Databases have assumed a crucial role in assimilating and storing information that could enable future discoveries. To this end, our group has developed two resources - Human Protein Reference Database (HPRD) and Human Proteinpedia - that provide integrated information pertaining to human proteins. These databases contain information on a number of features of proteins that have been discovered using various experimental methods. Human Proteinpedia was developed as a portal for community participation to annotate and share proteomic data using HPRD as the scaffold. It allows proteomic investigators to even share unpublished data and provides an effective medium for data sharing. As proteomic information reflects a direct view of cellular systems, proteomics is expected to complement other areas of biology such as genomics, transcriptomics, classical genetics, and chemical genetics in understanding the relationships among genome, gene functions, and living systems.

An evaluation of human protein-protein interaction data in the public domain

BackgroundProtein-protein interaction (PPI) databases have become a major resource for investigating biological networks and pathways in cells. A number of publicly available repositories for human PPIs are currently available. Each of these databases has their own unique features with a large variation in the type and depth of their annotations.ResultsWe analyzed the major publicly available primary databases that contain literature curated PPI information for human proteins. This included BIND, DIP, HPRD, IntAct, MINT, MIPS, PDZBase and Reactome databases. The number of binary non-redundant human PPIs ranged from 101 in PDZBase and 346 in MIPS to 11,367 in MINT and 36,617 in HPRD. The number of genes annotated with at least one interactor was 9,427 in HPRD, 4,975 in MINT, 4,614 in IntAct, 3,887 in BIND and <1,000 in the remaining databases. The number of literature citations for the PPIs included in the databases was 43,634 in HPRD, 11,480 in MINT, 10,331 in IntAct, 8,020 in BIND and <2,100 in the remaining databases.ConclusionGiven the importance of PPIs, we suggest that submission of PPIs to repositories be made mandatory by scientific journals at the time of manuscript submission as this will minimize annotation errors, promote standardization and help keep the information up to date. We hope that our analysis will help guide biomedical scientists in selecting the most appropriate database for their needs especially in light of the dramatic differences in their content.

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.

Viral immune modulators perturb the human molecular network by common and unique strategies

Viruses must enter host cells to replicate, assemble and propagate. Because of the restricted size of their genomes, viruses have had to evolve efficient ways of exploiting host cell processes to promote their own life cycles and also to escape host immune defence mechanisms. Many viral open reading frames (viORFs) with immune-modulating functions essential for productive viral growth have been identified across a range of viral classes. However, there has been no comprehensive study to identify the host factors with which these viORFs interact for a global perspective of viral perturbation strategies. Here we show that different viral perturbation patterns of the host molecular defence network can be deduced from a mass-spectrometry-based host-factor survey in a defined human cellular system by using 70 innate immune-modulating viORFs from 30 viral species. The 579 host proteins targeted by the viORFs mapped to an unexpectedly large number of signalling pathways and cellular processes, suggesting yet unknown mechanisms of antiviral immunity. We further experimentally verified the targets heterogeneous nuclear ribonucleoprotein U, phosphatidylinositol-3-OH kinase, the WNK (with-no-lysine) kinase family and USP19 (ubiquitin-specific peptidase 19) as vulnerable nodes in the host cellular defence system. Evaluation of the impact of viral immune modulators on the host molecular network revealed perturbation strategies used by individual viruses and by viral classes. Our data are also valuable for the design of broad and specific antiviral therapies.

Comprehensive Comparison of Collision Induced Dissociation and Electron Transfer Dissociation

Electron transfer dissociation (ETD) is a recently introduced mass spectrometric technique which has proven to be an excellent tool for the elucidation of labile post-translational modifications such as phosphorylation and O-GlcNAcylation of serine and threonine residues. However, unlike collision induced dissociation (CID), which has been studied for decades, the intricacies of ETD-based fragmentation have not yet been firmly established or systematically addressed. In this analysis, we have systematically compared the CID and ETD fragmentation patterns for the large majority of the peptides that do not contain such labile modifications. Using a standard 48 protein mix, we were able to measure false-positive rates for the experiments and also assess a large number of peptides for a detailed comparison of CID and ETD fragmentation pattern. Analysis of ∼19 000 peptides derived from both standard proteins and complex protein samples revealed that (i) CID identified 50% more peptides than ETD; (ii) ETD resulted in ∼20% increase in amino acid sequence coverage over CID; and (iii) combining CID and ETD fragmentation increased the sequence coverage for an average tryptic peptide to 92%. Interestingly, our analysis revealed that nearly 60% of all ETD-identified peptides carried two positive charges, which is in sharp contrast to what has been generally accepted. We also present a novel strategy for automatic validation of peptide assignments based on identification of a peptide by consecutive CID and ETD fragmentation in an alternating mode.

Human Proteinpedia: A unified discovery resource for proteomics research

Sharing proteomic data with the biomedical community through a unified proteomic resource, especially in the context of individual proteins, is a challenging prospect. We have developed a community portal, designated as Human Proteinpedia (http://www.humanproteinpedia.org/), for sharing both unpublished and published human proteomic data through the use of a distributed annotation system designed specifically for this purpose. This system allows laboratories to contribute and maintain protein annotations, which are also mapped to the corresponding proteins through the Human Protein Reference Database (HPRD; http://www.hprd.org/). Thus, it is possible to visualize data pertaining to experimentally validated posttranslational modifications (PTMs), protein isoforms, protein–protein interactions (PPIs), tissue expression, expression in cell lines, subcellular localization and enzyme substrates in the context of individual proteins. With enthusiastic participation of the proteomics community, the past 15 months have witnessed data contributions from more than 75 labs around the world including 2710 distinct experiments, >1.9 million peptides, >4.8 million MS/MS spectra, 150 368 protein expression annotations, 17 410 PTMs, 34 624 PPIs and 2906 subcellular localization annotations. Human Proteinpedia should serve as an integrated platform to store, integrate and disseminate such proteomic data and is inching towards evolving into a unified human proteomics resource.

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.