Babylakshmi Muthusamy

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.

Human protein reference database as a discovery resource for proteomics

The rapid pace at which genomic and proteomic data is being generated necessitates the development of tools and resources for managing data that allow integration of information from disparate sources. The Human Protein Reference Database (http://www.hprd.org) is a web-based resource based on open source technologies for protein information about several aspects of human proteins including protein-protein interactions, post-translational modifications, enzyme-substrate relationships and disease associations. This information was derived manually by a critical reading of the published literature by expert biologists and through bioinformatics analyses of the protein sequence. This database will assist in biomedical discoveries by serving as a resource of genomic and proteomic information and providing an integrated view of sequence, structure, function and protein networks in health and disease.

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.

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.

Human protein reference database and human proteinpedia as discovery resources for molecular biotechnology.

In the recent years, research in molecular biotechnology has transformed from being small scale studies targeted at a single or a small set of molecule(s) into a combination of high throughput discovery platforms and extensive validations. Such a discovery platform provided an unbiased approach which resulted in the identification of several novel genetic and protein biomarkers. High throughput nature of these investigations coupled with higher sensitivity and specificity of Next Generation technologies provided qualitatively and quantitatively richer biological data. These developments have also revolutionized biological research and speed of data generation. However, it is becoming difficult for individual investigators to directly benefit from this data because they are not easily accessible. Data resources became necessary to assimilate, store and disseminate information that could allow future discoveries. We have developed two resources—Human Protein Reference Database (HPRD) and Human Proteinpedia, which integrate knowledge relevant to human proteins. A number of protein features including protein–protein interactions, post-translational modifications, subcellular localization, and tissue expression, which have been studied using different strategies were incorporated in these databases. Human Proteinpedia also provides a portal for community participation to annotate and share proteomic data and uses HPRD as the scaffold for data processing. Proteomic investigators can even share unpublished data in Human Proteinpedia, which provides a meaningful platform 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, molecular biology, cloning, and classical genetics in understanding the relationships among multiple facets of biological systems.

SILAC-based quantitative proteomic approach to identify potential biomarkers from the esophageal squamous cell carcinoma secretome

The identification of secreted proteins that are differentially expressed between non-neoplastic and esophageal squamous cell carcinoma (ESCC) cells can provide potential biomarkers of ESCC. We used a SILAC-based quantitative proteomic approach to compare the secretome of ESCC cells with that of non-neoplastic esophageal squamous epithelial cells. Proteins were resolved by SDS-PAGE, and tandem mass spectrometry analysis (LC-MS/MS) of in-gel trypsin-digested peptides was carried out on a high-accuracy qTOF mass spectrometer. In total, we identified 441 proteins in the combined secretomes, including 120 proteins with >2-fold upregulation in the ESCC secretome vs. that of non-neoplastic esophageal squamous epithelial cells. In this study, several potential protein biomarkers previously known to be increased in ESCC including matrix metalloproteinase 1, transferrin receptor, and transforming growth factor beta-induced 68 kDa were identified as overexpressed in the ESCC-derived secretome. In addition, we identified several novel proteins that have not been previously reported to be associated with ESCC. Among the novel candidate proteins identified, protein disulfide isomerase family a member 3 (PDIA3), GDP dissociation inhibitor 2 (GDI2), and lectin galactoside binding soluble 3 binding protein (LGALS3BP) were further validated by immunoblot analysis and immunohistochemical labeling using tissue microarrays. This tissue microarray analysis showed overexpression of protein disulfide isomerase family a member 3, GDP dissociation inhibitor 2, and lectin galactoside binding soluble 3 binding protein in 93%, 93% and 87% of 137 ESCC cases, respectively. Hence, we conclude that these potential biomarkers are excellent candidates for further evaluation to test their role and efficacy in the early detection of ESCC.

A Proteomic Analysis of Human Hemodialysis Fluid

The vascular compartment is an easily accessible compartment that provides an opportunity to measure analytes for diagnostic, prognostic, or therapeutic indications. Both serum and plasma have been analyzed extensively by proteomic approaches in an effort to catalog all proteins and polypeptides. Limitations of such approaches in obtaining a comprehensive catalog of proteins include the fact that a handful of proteins constitute over 90% of plasma protein content and that the renal glomeruli filter out proteins and polypeptides that are smaller than 66 kDa from blood. We chose to study hemodialysis fluid because it contains a higher concentration of small proteins and polypeptides and is also simultaneously depleted of the most abundant proteins present in blood. Using gel electrophoresis in combination with LC-MS/MS, we identified 292 proteins of which greater than 70% had not been previously identified from serum or plasma. More than half of the proteins identified from the hemodialysis fluid were smaller than 40 kDa. We also found 50 N-terminally acetylated peptides that allowed us to unambiguously map the N termini of mature forms of the corresponding proteins. Several identified proteins, including cytokines, were only present as predicted transcripts in data bases and thus represent novel proteins. The proteins identified in this study could serve as biomarkers in serum using more sensitive methods such as ELISA-specific antibodies.

A proteogenomic analysis of Anopheles gambiae using high-resolution Fourier transform mass spectrometry

Anopheles gambiae is a major mosquito vector responsible for malaria transmission, whose genome sequence was reported in 2002. Genome annotation is a continuing effort, and many of the approximately 13,000 genes listed in VectorBase for Anopheles gambiae are predictions that have still not been validated by any other method. To identify protein-coding genes of An. gambiae based on its genomic sequence, we carried out a deep proteomic analysis using high-resolution Fourier transform mass spectrometry for both precursor and fragment ions. Based on peptide evidence, we were able to support or correct more than 6000 gene annotations including 80 novel gene structures and about 500 translational start sites. An additional validation by RT-PCR and cDNA sequencing was successfully performed for 105 selected genes. Our proteogenomic analysis led to the identification of 2682 genome search-specific peptides. Numerous cases of encoded proteins were documented in regions annotated as intergenic, introns, or untranslated regions. Using a database created to contain potential splice sites, we also identified 35 novel splice junctions. This is a first report to annotate the An. gambiae genome using high-accuracy mass spectrometry data as a complementary technology for genome annotation.

Comprehensive proteomic analysis of human bile

Bile serves diverse functions from metabolism to transport. In addition to acids and salts, bile is composed of proteins secreted or shed by the hepatobiliary system. Although there have been previous efforts to catalog biliary proteins, an in‐depth analysis of the bile proteome has not yet been reported. We carried out fractionation of non‐cancerous bile samples using a multipronged approach (SDS‐PAGE, SCX and OFFGEL) followed by MS analysis on an LTQ‐Orbitrap Velos mass spectrometer using high resolution at both MS and MS/MS levels. We identified 2552 proteins – the largest number of proteins reported in human bile till date. To our knowledge, there are no previous studies employing high‐resolution MS reporting a more detailed catalog of any body fluid proteome in a single study. We propose that extensive fractionation coupled to high‐resolution MS can be used as a standard methodology for in‐depth characterization of any body fluid. This catalog should serve as a baseline for the future studies aimed at discovering biomarkers from bile in gallbladder, hepatic, and biliary cancers.

A proteogenomic approach to map the proteome of an unsequenced pathogen - Leishmania donovani.

Visceral leishmaniasis or kala azar is the most severe form of leishmaniasis and is caused by the protozoan parasite Leishmania donovani. There is no published report on L. donovani genome sequence available till date, although the genome sequences of three related Leishmania species are already available. Thus, we took a proteogenomic approach to identify proteins from two different life stages of L. donovani. From our analysis of the promastigote (insect) and amastigote (human) stages of L. donovani, we identified a total of 22322 unique peptides from a homology‐based search against proteins from three Leishmania species. These peptides were assigned to 3711 proteins in L. infantum, 3287 proteins in L. major, and 2433 proteins in L. braziliensis. Of the 3711 L. donovani proteins that were identified, the expression of 1387 proteins was detectable in both life stages of the parasite, while 901 and 1423 proteins were identified only in promastigotes and amastigotes life stages, respectively. In addition, we also identified 13 N‐terminally and one C‐terminally extended proteins based on the proteomic data search against the six‐frame translated genome of the three related Leishmania species. Here, we report results from proteomic profiling of L. donovani, an organism with an unsequenced genome.