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Dive into the research topics where Subramanian Shankar is active.

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Featured researches published by Subramanian Shankar.


Nature | 2014

A draft map of the human proteome

Min Sik Kim; Sneha M. Pinto; Derese Getnet; Raja Sekhar Nirujogi; Srikanth S. Manda; Raghothama Chaerkady; Dhanashree S. Kelkar; Ruth Isserlin; Shobhit Jain; Joji Kurian Thomas; Babylakshmi Muthusamy; Pamela Leal-Rojas; Praveen Kumar; Nandini A. Sahasrabuddhe; Lavanya Balakrishnan; Jayshree Advani; Bijesh George; Santosh Renuse; Lakshmi Dhevi N. Selvan; Arun H. Patil; Vishalakshi Nanjappa; Aneesha Radhakrishnan; Samarjeet Prasad; Tejaswini Subbannayya; Rajesh Raju; Manish Kumar; Sreelakshmi K. Sreenivasamurthy; Arivusudar Marimuthu; Gajanan Sathe; Sandip Chavan

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.


Nucleic Acids Research | 2014

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

Vishalakshi Nanjappa; Joji Kurian Thomas; Arivusudar Marimuthu; Babylakshmi Muthusamy; Aneesha Radhakrishnan; Rakesh K. Sharma; Aafaque Ahmad Khan; Lavanya Balakrishnan; Nandini A. Sahasrabuddhe; Satwant Kumar; Binit N Jhaveri; Kaushal Vinaykumar Sheth; Ramesh Kumar Khatana; Patrick G. Shaw; S. Srikanth; Premendu P. Mathur; Subramanian Shankar; Dindagur Nagaraja; Rita Christopher; Suresh Mathivanan; Rajesh Raju; Ravi Sirdeshmukh; Aditi Chatterjee; Richard J. Simpson; H. C. Harsha; Akhilesh Pandey; T. S. Keshava Prasad

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.


Clinical Proteomics | 2014

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

Lavanya Balakrishnan; Mitali Bhattacharjee; Sartaj Ahmad; Raja Sekhar Nirujogi; Santosh Renuse; Yashwanth Subbannayya; Arivusudar Marimuthu; S. Srikanth; Rajesh Raju; Mukesh Dhillon; Navjyot Kaur; Ramesh Jois; Vivek Vasudev; Yl Ramachandra; Nandini A. Sahasrabuddhe; T. S. Keshava Prasad; S. Sujatha Mohan; Harsha Gowda; Subramanian Shankar; Akhilesh Pandey

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.


Clinical Proteomics | 2014

Proteomic analysis of human osteoarthritis synovial fluid

Lavanya Balakrishnan; Raja Sekhar Nirujogi; Sartaj Ahmad; Mitali Bhattacharjee; Srikanth S. Manda; Santosh Renuse; Dhanashree S. Kelkar; Yashwanth Subbannayya; Rajesh Raju; Renu Goel; Joji Kurian Thomas; Navjyot Kaur; Mukesh Dhillon; Shantal Gupta Tankala; Ramesh Jois; Vivek Vasdev; Yl Ramachandra; Nandini A. Sahasrabuddhe; T. S. Keshava Prasad; S. Sujatha Mohan; Harsha Gowda; Subramanian Shankar; Akhilesh Pandey

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.


Database | 2011

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

Rajesh Raju; Lavanya Balakrishnan; Vishalakshi Nanjappa; Mitali Bhattacharjee; Derese Getnet; Babylakshmi Muthusamy; Joji Kurian Thomas; Jyoti Sharma; B. Abdul Rahiman; H. C. Harsha; Subramanian Shankar; T. S. Keshava Prasad; S. Sujatha Mohan; Gary D. Bader; Mohan R. Wani; Akhilesh Pandey

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


Journal of Cell Communication and Signaling | 2015

A knowledgebase resource for interleukin-17 family mediated signaling.

Jyoti Sharma; Lavanya Balakrishnan; Keshava K. Datta; Nandini A. Sahasrabuddhe; Aafaque Ahmad Khan; Apeksha Sahu; Anish Singhal; Derese Getnet; Rajesh Raju; Aditi Chatterjee; Harsha Gowda; T. S. Keshava Prasad; Subramanian Shankar; Akhilesh Pandey

Interleukin-17 (IL-17) belongs to a relatively new family of cytokines that has garnered attention as the signature cytokine of Th17 cells. This cytokine family consists of 6 ligands, which bind to 5 receptor subtypes and induce downstream signaling. Although the receptors are ubiquitously expressed, cellular responses to ligands vary across tissues. The cytokine family is associated with various autoimmune disorders including rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease, asthma and psoriasis in addition to being implicated in the pathogenesis of cancer. In addition, this family plays a role in host defense against bacterial and fungal infections. The signaling mechanisms of the IL-17 family of proinflammatory cytokines are not well explored. In this study, we present a resource of literature-annotated reactions induced by IL-17. The reactions are catalogued under 5 categories, namely; molecular association, catalysis, transport, activation/inhibition and gene regulation. A total of 93 molecules and 122 reactions have been annotated. The IL-17 pathway is freely available through NetPath, a resource of signal transduction pathways previously developed by our group.


Journal of Cell Communication and Signaling | 2016

A network map of Interleukin-10 signaling pathway.

Renu Verma; Lavanya Balakrishnan; Kusum Sharma; Aafaque Ahmad Khan; Jayshree Advani; Harsha Gowda; Srikanth Tripathy; Mrutyunjay Suar; Akhilesh Pandey; Sheetal Gandotra; T. S. Keshava Prasad; Subramanian Shankar

Interleukin-10 (IL-10) is an anti-inflammatory cytokine with important immunoregulatory functions. It is primarily secreted by antigen-presenting cells such as activated T-cells, monocytes, B-cells and macrophages. In biologically functional form, it exists as a homodimer that binds to tetrameric heterodimer IL-10 receptor and induces downstream signaling. IL-10 is associated with survival, proliferation and anti-apoptotic activities of various cancers such as Burkitt lymphoma, non-Hodgkins lymphoma and non-small scell lung cancer. In addition, it plays a central role in survival and persistence of intracellular pathogens such as Leishmania donovani, Mycobacterium tuberculosis and Trypanosoma cruzi inside the host. The signaling mechanisms of IL-10 cytokine are not well explored and a well annotated pathway map has been lacking. To this end, we developed a pathway resource by manually annotating the IL-10 induced signaling molecules derived from literature. The reactions were categorized under molecular associations, activation/inhibition, catalysis, transport and gene regulation. In all, 37 molecules and 76 reactions were annotated. The IL-10 signaling pathway can be freely accessed through NetPath, a resource of signal transduction pathways previously developed by our group.


Clinical Proteomics | 2016

Synovial fluid proteome in rheumatoid arthritis

Mitali Bhattacharjee; Lavanya Balakrishnan; Santosh Renuse; Jayshree Advani; Renu Goel; Gajanan Sathe; T. S. Keshava Prasad; Bipin G. Nair; Ramesh Jois; Subramanian Shankar; Akhilesh Pandey

BackgroundRheumatoid arthritis (RA) is a chronic autoinflammatory disorder that affects small joints. Despite intense efforts, there are currently no definitive markers for early diagnosis of RA and for monitoring the progression of this disease, though some of the markers like anti CCP antibodies and anti vimentin antibodies are promising. We sought to catalogue the proteins present in the synovial fluid of patients with RA. It was done with the aim of identifying newer biomarkers, if any, that might prove promising in future.MethodsTo enrich the low abundance proteins, we undertook two approaches—multiple affinity removal system (MARS14) to deplete some of the most abundant proteins and lectin affinity chromatography for enrichment of glycoproteins. The peptides were analyzed by LC–MS/MS on a high resolution Fourier transform mass spectrometer.ResultsThis effort was the first total profiling of the synovial fluid proteome in RA that led to identification of 956 proteins. From the list, we identified a number of functionally significant proteins including vascular cell adhesion molecule-1, S100 proteins, AXL receptor protein tyrosine kinase, macrophage colony stimulating factor (M-CSF), programmed cell death ligand 2 (PDCD1LG2), TNF receptor 2, (TNFRSF1B) and many novel proteins including hyaluronan-binding protein 2, semaphorin 4A (SEMA4D) and osteoclast stimulating factor 1. Overall, our findings illustrate the complex and dynamic nature of RA in which multiple pathways seems to be participating actively.ConclusionsThe use of high resolution mass spectrometry thus, enabled identification of proteins which might be critical to the progression of RA.


Clinical Proteomics | 2013

A multilectin affinity approach for comparative glycoprotein profiling of rheumatoid arthritis and spondyloarthropathy

Mitali Bhattacharjee; Rakesh K. Sharma; Renu Goel; Lavanya Balakrishnan; Santosh Renuse; Jayshree Advani; Shantal Tankala Gupta; Renu Verma; Sneha M. Pinto; Nirujogi Raja Sekhar; Bipin G. Nair; T. S. Keshava Prasad; H. C. Harsha; Ramesh Jois; Subramanian Shankar; Akhilesh Pandey

BackgroundArthritis refers to inflammation of joints and includes common disorders such as rheumatoid arthritis (RA) and spondyloarthropathies (SpAs). These diseases differ mainly in terms of their clinical manifestations and the underlying pathogenesis. Glycoproteins in synovial fluid might reflect the disease activity status in the joints affected by arthritis; yet they have not been systematically studied previously. Although markers have been described for assisting in the diagnosis of RA, there are currently no known biomarkers for SpA.Materials and methodsWe sought to determine the relative abundance of glycoproteins in RA and SpA by lectin affinity chromatography coupled to iTRAQ labeling and LC-MS/MS analysis. We also used ELISA to validate the overexpression of VCAM-1, one of the candidate proteins identified in this study, in synovial fluid from RA patients.Results and discussionWe identified proteins that were previously reported to be overexpressed in RA including metalloproteinase inhibitor 1 (TIMP1), myeloperoxidase (MPO) and several S100 proteins. In addition, we discovered several novel candidates that were overexpressed in SpA including Apolipoproteins C-II and C-III and the SUN domain-containing protein 3 (SUN3). Novel molecules found overexpressed in RA included extracellular matrix protein 1 (ECM1) and lumican (LUM). We validated one of the candidate biomarkers, vascular cell adhesion molecule 1 (VCAM1), in 20 RA and SpA samples using ELISA and confirmed its overexpression in RA (p-value <0.01). Our quantitative glycoproteomic approach to study arthritic disorders should open up new avenues for additional proteomics-based discovery studies in rheumatological disorders.


Indian Journal of Rheumatology | 2010

Indian Rheumatology Association consensus statement on the diagnosis and treatment of axial spondyloarthropathies

An Malaviya; Subramanian Shankar; Vivek Arya; V Dhir; V Agarwal; S Pandya; K Shanmuganandan; Vp Chaturvedi; Cj Das

1A&R Clinic and ISIC Superspeciality Hospital, New Delhi, 2Department of Internal Medicine, Armed Forces Medical College, Pune, 3Department of Medicine, PGIMER and Dr RML Hospital, New Delhi, 4Department of Medicine, All India Institute of Medical Sciences, New Delhi, 5Department of Clinical Immunology, SGPGIMS, Lucknow, 6Vedant, Nr Samved Hospital Ahmedabad, Gujarat, 7Department of Medicine, Army Base Hospital, Basistha, Guwahati, 8Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi. Correspondence: Dr AN Malaviya, email: [email protected] EPIDEMIOLOGY OF SPONDYLOARTHROPATHY

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Akhilesh Pandey

Johns Hopkins University School of Medicine

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Velu Nair

Armed Forces Medical College

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Santosh Renuse

Amrita Vishwa Vidyapeetham

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