Joji Kurian Thomas

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.

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.

Proteomic analysis of human osteoarthritis synovial fluid

BackgroundOsteoarthritis is a chronic musculoskeletal disorder characterized mainly by progressive degradation of the hyaline cartilage. Patients with osteoarthritis often postpone seeking medical help, which results in the diagnosis being made at an advanced stage of cartilage destruction. Sustained efforts are needed to identify specific markers that might help in early diagnosis, monitoring disease progression and in improving therapeutic outcomes. We employed a multipronged proteomic approach, which included multiple fractionation strategies followed by high resolution mass spectrometry analysis to explore the proteome of synovial fluid obtained from osteoarthritis patients. In addition to the total proteome, we also enriched glycoproteins from synovial fluid using lectin affinity chromatography.ResultsWe identified 677 proteins from synovial fluid of patients with osteoarthritis of which 545 proteins have not been previously reported. These novel proteins included ADAM-like decysin 1 (ADAMDEC1), alanyl (membrane) aminopeptidase (ANPEP), CD84, fibulin 1 (FBLN1), matrix remodelling associated 5 (MXRA5), secreted phosphoprotein 2 (SPP2) and spondin 2 (SPON2). We identified 300 proteins using lectin affinity chromatography, including the glycoproteins afamin (AFM), attractin (ATRN), fibrillin 1 (FBN1), transferrin (TF), tissue inhibitor of metalloproteinase 1 (TIMP1) and vasorin (VSN). Gene ontology analysis confirmed that a majority of the identified proteins were extracellular and are mostly involved in cell communication and signaling. We also confirmed the expression of ANPEP, dickkopf WNT signaling pathway inhibitor 3 (DKK3) and osteoglycin (OGN) by multiple reaction monitoring (MRM) analysis of osteoarthritis synovial fluid samples.ConclusionsWe present an in-depth analysis of the synovial fluid proteome from patients with osteoarthritis. We believe that the catalog of proteins generated in this study will further enhance our knowledge regarding the pathophysiology of osteoarthritis and should assist in identifying better biomarkers for early diagnosis.

A comprehensive manually curated reaction map of RANKL/RANK-signaling pathway.

Receptor activator of nuclear factor-kappa B ligand (RANKL) is a member of tumor necrosis factor (TNF) superfamily that plays a key role in the regulation of differentiation, activation and survival of osteoclasts and also in tumor cell migration and bone metastasis. Osteoclast activation induced by RANKL regulates hematopoietic stem cell mobilization as part of homeostasis and host defense mechanisms thereby linking regulation of hematopoiesis with bone remodeling. Binding of RANKL to its receptor, Receptor activator of nuclear factor-kappa B (RANK) activates molecules such as NF-kappa B, mitogen activated protein kinase (MAPK), nuclear factor of activated T cells (NFAT) and phosphatidyl 3-kinase (PI3K). Although the molecular and cellular roles of these molecules have been reported previously, a systematic cataloging of the molecular events induced by RANKL/RANK interaction has not been attempted. Here, we present a comprehensive reaction map of the RANKL/RANK-signaling pathway based on an extensive manual curation of the published literature. We hope that the curated RANKL/RANK-signaling pathway model would enable new biomedical discoveries, which can provide novel insights into disease processes and development of novel therapeutic interventions. Database URL: http://www.netpath.org/pathways?path_id=NetPath_21

Access Guide to Human Proteinpedia

Human Proteinpedia (http://www.humanproteinpedia.org) is a publicly available proteome repository for sharing human protein data derived from multiple experimental platforms. It incorporates diverse features of the human proteome including protein‐protein interactions, enzyme‐substrate relationships, PTMs, subcellular localization, and expression of proteins in various human tissues and cell lines in diverse biological conditions including diseases. Through a publicly distributed annotation system developed especially for proteomic data, investigators across the globe can upload, view, and edit proteomic data even before they are published. Inclusion of information on investigators and laboratories that generated the data, as well as visualization of tandem mass spectra, stained tissue sections, protein/peptide microarrays, fluorescent micrographs, and western blots, ensures quality of proteomic data assimilated in Human Proteinpedia. Many of the protein annotations submitted to Human Proteinpedia have also been made available to the scientific community through Human Protein Reference Database (http://www.hprd.org), another resource developed by our group. In this protocol, we describe how to submit, edit, and retrieve proteomic data in Human Proteinpedia. Curr. Protoc. Bioinform. 41:1.21.1‐1.21.15.

NetSlim: high-confidence curated signaling maps

We previously developed NetPath as a resource for comprehensive manually curated signal transduction pathways. The pathways in NetPath contain a large number of molecules and reactions which can sometimes be difficult to visualize or interpret given their complexity. To overcome this potential limitation, we have developed a set of more stringent curation and inclusion criteria for pathway reactions to generate high-confidence signaling maps. NetSlim is a new resource that contains this ‘core’ subset of reactions for each pathway for easy visualization and manipulation. The pathways in NetSlim are freely available at http://www.netpath.org/netslim. Database URL: www.netpath.org/netslim

Pancreatic Cancer Database: An integrative resource for pancreatic cancer

Pancreatic cancer is the fourth leading cause of cancer-related death in the world. The etiology of pancreatic cancer is heterogeneous with a wide range of alterations that have already been reported at the level of the genome, transcriptome, and proteome. The past decade has witnessed a large number of experimental studies using high-throughput technology platforms to identify genes whose expression at the transcript or protein levels is altered in pancreatic cancer. Based on expression studies, a number of molecules have also been proposed as potential biomarkers for diagnosis and prognosis of this deadly cancer. Currently, there are no repositories which provide an integrative view of multiple Omics data sets from published research on pancreatic cancer. Here, we describe the development of a web-based resource, Pancreatic Cancer Database (http://www.pancreaticcancerdatabase.org), as a unified platform for pancreatic cancer research. PCD contains manually curated information pertaining to quantitative alterations in miRNA, mRNA, and proteins obtained from small-scale as well as high-throughput studies of pancreatic cancer tissues and cell lines. We believe that PCD will serve as an integrative platform for scientific community involved in pancreatic cancer research.

A pathway map of prolactin signaling.

Prolactin (PRL) is a pleiotropic polypeptide hormone secreted primarily by the lactotrophic cells of anterior pituitary gland in vertebrates (Freeman et al. 2000). This hormone family includes placental lactogen (PL) and growth hormone (GH) (Corbacho et al. 2002). Prolactin plays a major role in lactation and reproduction and has been shown to have a multitude of effects relating to growth, development, metabolism, immunoregulation and protection (Ben-Jonathan et al. 2006). The prolactin signaling pathway is initiated by the binding of prolactin with the prolactin receptor (PRLR), a member of class I cytokine receptor superfamily (Binart et al. 2000), which is expressed in a variety of tissues. The PRLR comprises of an extracellular ligand binding domain, a transmembrane domain and an intracellular domain. The PRLR lacks intrinsic kinase activity and transduces signal through kinases that interact with its cytoplasmic tail. Three constitutively active variants of the receptor have been reported in humans (Goffin et al. 2010). Though the signaling reactions downstream of the longest isoform of prolactin receptor have been well established, little is known about prolactin signaling initiated by six other isoforms (Bouilly et al. 2011). Studies also indicate that binding affinity of the human prolactin receptor to nonhuman prolactin is lower than human prolactin (Utama et al. 2009). The prolactin receptor also binds to hPL and hGH leading to the activation of downstream pathways. However, we have not considered these reactions in the current study. This study reports only those reactions, which occur upon stimulation of prolactin receptor with prolactin, based on the criteria described previously (Nanjappa et al. 2011). Availability of signaling pathway information is useful to the biomedical research community, especially for systems biology approaches. Considering this, we have developed ‘NetPath’ as a resource of ligand-receptor specific signal transduction pathways (Kandasamy et al. 2010). As a part of this, we have carried out manual annotation of available information from the published literature for ligand-receptor signaling pathways (Raju et al. 2011a; Nanjappa et al. 2011; Telikicherla et al. 2011; Goel et al. 2012). Similarly, in this study, we enriched publicly available information pertaining to prolactin-prolactin receptor dependent signaling pathways and also generated a graphic map depicting the prolactin signaling pathway.

Signaling network of Oncostatin M pathway

Oncostatin M (OSM), belonging to the IL-6 family of cytokines (Heinrich et al. 2003), was first reported and purified from U937 monocytic cells (Zarling et al. 1986; Ensoli et al. 1999; Hasegawa et al. 1999). In normal physiological condition, OSM is associated with multiple biological processes and cellular responses including growth, differentiation, and inflammation However, anti-proliferative activity of OSM against breast cancer cell line generated the interest of biomedical community on this molecule (Douglas et al. 1997, 1998). OSM was also found associated with pathological conditions such as proliferation of ovarian cancer cells (Taga and Kishimoto 1997), prostate cancer 22Rv1 cells (Hoffman et al. 1996), up-regulation of the ER chaperone Grp78/BiP in the liver cells, atherosclerotic lesions, ischemic heart disease and rheumatoid arthritis (Linsley et al. 1990; Dunham et al. 1999). The dual role of OSM in either inducing or inhibiting the proliferation of various types of cells called upon the scientific community to investigate role of OSM in various physiological and experimental contexts in detail. However, diverse molecular level information pertaining to OSM signaling is not available in a centralized resource. Therefore, we have systematically gathered and curated molecular information from literature and created a public resource for OSM induced signaling events. We integrated OSM signaling pathway into NetPath (Kandasamy et al. 2010), which is a public resource of human signaling pathways. OSM is known to mediate its biological effects by binding to two distinct heterodimers of gp130 with either leukemia inhibiting factor receptor (LIFR) or OSM receptor-beta (OSMR-beta) (Thoma et al. 1994). Former heterodimer between gp130 and LIFR is called type I receptor complex and the latter between gp130 and OSMR-beta is called type II receptor complex. Type I receptor can bind to either OSM or leukemia inhibiting factor, whereas type II receptor has more affinity towards OSM (O’Hara et al. 2003). The binding of OSM to either gp130/OSMR-beta or gp130/LIFR induces the activation of Janus Kinase family members through tyrosine phosphorylation (Tanaka and Miyajima 2003). The activated JAK family members in turn induce the activation of Signal Transduction and Activator of Transcription (STAT) proteins (Schaefer et al. 2000). Alternatively, the activated receptors can also activate mitogen-activated protein kinase (MAPK) pathway (Van Wagoner et al. 2000) and PI3K/AKT pathways (Arita et al. 2008). It was also reported that OSM bring about ligand-induced receptor degradation of gp130, OSMR-beta, and LIFR before enhancing the synthesis of the receptor subunits (Blanchard et al. 2001).

A pathway map of glutamate metabolism

Glutamate metabolism plays a vital role in biosynthesis of nucleic acids and proteins. It is also associated with a number of different stress responses. Deficiency of enzymes involved in glutamate metabolism is associated with various disorders including gyrate atrophy, hyperammonemia, hemolytic anemia, γ-hydoxybutyric aciduria and 5-oxoprolinuria. Here, we present a pathway map of glutamate metabolism representing metabolic intermediates in the pathway, 107 regulator molecules, 9 interactors and 3 types of post-translational modifications. This pathway map provides detailed information about enzyme regulation, protein-enzyme interactions, post-translational modifications of enzymes and disorders due to enzyme deficiency. The information included in the map was based on published experimental evidence reported from mammalian systems.