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1. Correction: Biochemical characterization of protease activity of Nsp3 from SARS-CoV-2 and its inhibition by nanobodies

Author

Armstrong, Lee A., primary, Lange, Sven M., additional, Cesare, Virginia De, additional, Matthews, Stephen P., additional, Nirujogi, Raja Sekhar, additional, Cole, Isobel, additional, Hope, Anthony, additional, Cunningham, Fraser, additional, Toth, Rachel, additional, Mukherjee, Rukmini, additional, Bojkova, Denisa, additional, Gruber, Franz, additional, Gray, David, additional, Wyatt, Paul G., additional, Cinatl, Jindrich, additional, Dikic, Ivan, additional, Davies, Paul, additional, and Kulathu, Yogesh, additional

Published
2024
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10. A draft map of the human proteome

Author

Kim, Min-Sik, Pinto, Sneha M., Getnet, Derese, Nirujogi, Raja Sekhar, Manda, Srikanth S., Chaerkady, Raghothama, and Madugundu, Anil K.

Subjects
Proteomics -- Methods, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

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 draft map of the human proteome is presented here, accounting for over 80% of the annotated protein-coding genes in humans; some novel protein-coding regions, including translated pseudogenes, non-coding RNAs and upstream open reading frames, are identified. Mapping the human proteome More than a decade after publication of the draft human genome sequence, there is no direct equivalent for the human proteome. But in this issue of Nature two groups present mass spectrometry-based analysis of human tissues, body fluids and cells mapping the large majority of the human proteome. Akhilesh Pandey and colleagues identified 17,294 protein-coding genes and provide evidence of tissue- and cell-restricted proteins through expression profiling. They highlight the importance of proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions. The data set is available on http://www.humanproteomemap.org. Bernhard Kuster and colleagues have assembled protein evidence for 18,097 genes in ProteomicsDB (available on https://www.proteomicsdb.org) and highlight the utility of the data, for example the identification of hundreds of translated lincRNAs, drug-sensitivity markers and discovering the quantitative relationship between mRNA and protein levels in tissues. Elsewhere in this issue, Vivien Marx reports on a third major proteomics project, the antibody-based Human Protein Atlas programme (http://www.proteinatlas.org/)., Author(s): Min-Sik Kim [sup.1] [sup.2] , Sneha M. Pinto [sup.3] , Derese Getnet [sup.1] [sup.4] , Raja Sekhar Nirujogi [sup.3] , Srikanth S. Manda [sup.3] , Raghothama Chaerkady [sup.1] [sup.2] [...]

Published
2014
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11. Biochemical characterization of protease activity of Nsp3 from SARS-CoV-2 and its inhibition by nanobodies

Author

Armstrong, Lee A., primary, Lange, Sven M., additional, Dee Cesare, Virginia, additional, Matthews, Stephen P., additional, Nirujogi, Raja Sekhar, additional, Cole, Isobel, additional, Hope, Anthony, additional, Cunningham, Fraser, additional, Toth, Rachel, additional, Mukherjee, Rukmini, additional, Bojkova, Denisa, additional, Gruber, Franz, additional, Gray, David, additional, Wyatt, Paul G., additional, Cinatl, Jindrich, additional, Dikic, Ivan, additional, Davies, Paul, additional, and Kulathu, Yogesh, additional

Published
2021
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12. NetSlim: high-confidence curated signaling maps.

Author

Rajesh Raju, Vishalakshi Nanjappa, Lavanya Balakrishnan, Aneesha Radhakrishnan, Joji Kurian Thomas, Jyoti Sharma, Maozhen Tian, Shyam Mohan Palapetta, Tejaswini Subbannayya, Nirujogi Raja Sekhar, Babylakshmi Muthusamy, Renu Goel, Yashwanth Subbannayya, Deepthi Telikicherla, Mitali Bhattacharjee, Sneha M. Pinto, Nazia Syed, Srinivas Manda Srikanth, Gajanan J. Sathe, Sartaj Ahmad, Sandip N. Chavan, Ghantasala S. Sameer Kumar, Arivusudar Marimuthu, T. S. Keshava Prasad, H. C. Harsha, B. Abdul Rahiman, Osamu Ohara, Gary D. Bader, S. Sujatha Mohan, William P. Schiemann, and Akhilesh Pandey

Published
2011
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13. Complement and Coagulation Cascades are Potentially Involved in Dopaminergic Neurodegeneration in α-Synuclein-Based Mouse Models of Parkinson’s Disease

Author

Ma, Shi-Xun, primary, Seo, Bo Am, additional, Kim, Donghoon, additional, Xiong, Yulan, additional, Kwon, Seung-Hwan, additional, Brahmachari, Saurav, additional, Kim, Sangjune, additional, Kam, Tae-In, additional, Nirujogi, Raja Sekhar, additional, Kwon, Sang Ho, additional, Dawson, Valina L., additional, Dawson, Ted M., additional, Pandey, Akhilesh, additional, Na, Chan Hyun, additional, and Ko, Han Seok, additional

Published
2021
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14. A multi-omic analysis of human naïve CD4+ T cells.

Author

Christopher J. Mitchell, Derese Getnet, Min Sik Kim, Srinivas Manda Srikanth, Praveen Kumar, Tai-Chung Huang, Sneha M. Pinto, Nirujogi Raja Sekhar, Mio Iwasaki, Patrick G. Shaw, Xinyan Wu, Jun Zhong, Raghothama Chaerkady, Arivusudar Marimuthu, Babylakshmi Muthusamy, Nandini A. Sahasrabuddhe, Rajesh Raju, Caitlyn Bowman, Ludmila V. Danilova, Jevon Cutler, Dhanashree S. Kelkar, Charles G. Drake, T. S. Keshava Prasad, Luigi Marchionni, Peter N. Murakami, Alan F. Scott, Leming Shi, Jean Thierry-Mieg, Danielle Thierry-Mieg, Rafael A. Irizarry, Leslie Cope, Yasushi Ishihama, Charles Wang, Harsha Gowda, and Akhilesh Pandey

Published
2015
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15. PASS-DIA: A Data-Independent Acquisition Approach for Discovery Studies

Author

Mun, Dong-Gi, primary, Renuse, Santosh, additional, Saraswat, Mayank, additional, Madugundu, Anil, additional, Udainiya, Savita, additional, Kim, Hokeun, additional, Park, Sung-Kyu Robin, additional, Zhao, Hui, additional, Nirujogi, Raja Sekhar, additional, Na, Chan Hyun, additional, Kannan, Nagarajan, additional, Yates, John R., additional, Lee, Sang-Won, additional, and Pandey, Akhilesh, additional

Published
2020
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17. Complement and coagulation cascades are potentially involved in dopaminergic neurodegeneration in α-synuclein-based mouse models of Parkinson’s disease

Author

Ma, Shi-Xun, primary, Kim, Donghoon, additional, Xiong, Yulan, additional, Kwon, Seung-Hwan, additional, Brahmachari, Saurav, additional, Kim, Sangjune, additional, Kam, Tae-In, additional, Nirujogi, Raja Sekhar, additional, Kwon, Sang Ho, additional, Dawson, Valina L., additional, Dawson, Ted M., additional, Pandey, Akhilesh, additional, Na, Chan Hyun, additional, and Ko, Han Seok, additional

Published
2020
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18. Integrated Transcriptomic and Proteomic Analysis of Primary Human Umbilical Vein Endothelial Cells

Author

Madugundu, Anil K., primary, Na, Chan Hyun, additional, Nirujogi, Raja Sekhar, additional, Renuse, Santosh, additional, Kim, Kwang Pyo, additional, Burns, Kathleen H., additional, Wilks, Christopher, additional, Langmead, Ben, additional, Ellis, Shannon E., additional, Collado‐Torres, Leonardo, additional, Halushka, Marc K., additional, Kim, Min‐Sik, additional, and Pandey, Akhilesh, additional

Published
2019
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21. Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

Author

Prasad, T. S. Keshava, Mohanty, Ajeet Kumar, Kumar, Manish, Sreenivasamurthy, Sreelakshmi K., Dey, Gourav, Nirujogi, Raja Sekhar, Pinto, Sneha M., Madugundu, Anil K., Pati, Arun H., Advani, Jayshree, Manda, Srikanth S., Gupta, Manoj Kumar, Dwivedi, Sutopa B., Kelkar, Dhanashree S., Hall, Brantley, Jiang, Xiaofang, Peery, Ashley, Rajagopalan, Pavithra, Yelamanchi, Soujanya D., Solanki, Hitendra S., Raja, Remya, Sathe, Gajanan J., Chavan, Sandip, Verma, Renu, Patel, Krishna M., Jain, Ankit P., Syed, Nazia, Datta, Keshava K., Khan, Aafaque Ahmed, Dammalli, Manjunath, Jayaram, Savita, Radhakrishnan, Aneesha, Mitchell, Christopher J., Na, Chan-Hyun, Kumar, Nirbhay, Sinnis, Photini, Sharakhov, Igor V., Wang, Charles, Gowda, Harsha, Tu, Zhijian Jake, Kumar, Ashwani, Pandey, Akhilesh, Prasad, T. S. Keshava, Mohanty, Ajeet Kumar, Kumar, Manish, Sreenivasamurthy, Sreelakshmi K., Dey, Gourav, Nirujogi, Raja Sekhar, Pinto, Sneha M., Madugundu, Anil K., Pati, Arun H., Advani, Jayshree, Manda, Srikanth S., Gupta, Manoj Kumar, Dwivedi, Sutopa B., Kelkar, Dhanashree S., Hall, Brantley, Jiang, Xiaofang, Peery, Ashley, Rajagopalan, Pavithra, Yelamanchi, Soujanya D., Solanki, Hitendra S., Raja, Remya, Sathe, Gajanan J., Chavan, Sandip, Verma, Renu, Patel, Krishna M., Jain, Ankit P., Syed, Nazia, Datta, Keshava K., Khan, Aafaque Ahmed, Dammalli, Manjunath, Jayaram, Savita, Radhakrishnan, Aneesha, Mitchell, Christopher J., Na, Chan-Hyun, Kumar, Nirbhay, Sinnis, Photini, Sharakhov, Igor V., Wang, Charles, Gowda, Harsha, Tu, Zhijian Jake, Kumar, Ashwani, and Pandey, Akhilesh

Abstract

Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions,192 novel protein start sites,19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted "noncoding RNAs" to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes.

Published
2017
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22. Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

Author

Biochemistry, Entomology, Prasad, T. S. Keshava, Mohanty, Ajeet Kumar, Kumar, Manish, Sreenivasamurthy, Sreelakshmi K., Dey, Gourav, Nirujogi, Raja Sekhar, Pinto, Sneha M., Madugundu, Anil K., Pati, Arun H., Advani, Jayshree, Manda, Srikanth S., Gupta, Manoj Kumar, Dwivedi, Sutopa B., Kelkar, Dhanashree S., Hall, Brantley, Jiang, Xiaofang, Peery, Ashley, Rajagopalan, Pavithra, Yelamanchi, Soujanya D., Solanki, Hitendra S., Raja, Remya, Sathe, Gajanan J., Chavan, Sandip, Verma, Renu, Patel, Krishna M., Jain, Ankit P., Syed, Nazia, Datta, Keshava K., Khan, Aafaque Ahmed, Dammalli, Manjunath, Jayaram, Savita, Radhakrishnan, Aneesha, Mitchell, Christopher J., Na, Chan-Hyun, Kumar, Nirbhay, Sinnis, Photini, Sharakhov, Igor V., Wang, Charles, Gowda, Harsha, Tu, Zhijian Jake, Kumar, Ashwani, Pandey, Akhilesh, Biochemistry, Entomology, Prasad, T. S. Keshava, Mohanty, Ajeet Kumar, Kumar, Manish, Sreenivasamurthy, Sreelakshmi K., Dey, Gourav, Nirujogi, Raja Sekhar, Pinto, Sneha M., Madugundu, Anil K., Pati, Arun H., Advani, Jayshree, Manda, Srikanth S., Gupta, Manoj Kumar, Dwivedi, Sutopa B., Kelkar, Dhanashree S., Hall, Brantley, Jiang, Xiaofang, Peery, Ashley, Rajagopalan, Pavithra, Yelamanchi, Soujanya D., Solanki, Hitendra S., Raja, Remya, Sathe, Gajanan J., Chavan, Sandip, Verma, Renu, Patel, Krishna M., Jain, Ankit P., Syed, Nazia, Datta, Keshava K., Khan, Aafaque Ahmed, Dammalli, Manjunath, Jayaram, Savita, Radhakrishnan, Aneesha, Mitchell, Christopher J., Na, Chan-Hyun, Kumar, Nirbhay, Sinnis, Photini, Sharakhov, Igor V., Wang, Charles, Gowda, Harsha, Tu, Zhijian Jake, Kumar, Ashwani, and Pandey, Akhilesh

Abstract

Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions,192 novel protein start sites,19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted "noncoding RNAs" to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes.

Published
2017

23. Mutation-Specific and Common Phosphotyrosine Signatures of KRASG12D and G13D Alleles

Author

Tahir, Raiha, Renuse, Santosh, Udainiya, Savita, Madugundu, Anil K., Cutler, Jevon A., Nirujogi, Raja Sekhar, Na, Chan Hyun, Xu, Yaoyu, Wu, Xinyan, and Pandey, Akhilesh

Abstract

KRASis one of the most frequently mutated genes across all cancer subtypes. Two of the most frequent oncogenic KRASmutations observed in patients result in glycine to aspartic acid substitution at either codon 12 (G12D) or 13 (G13D). Although the biochemical differences between these two predominant mutations are not fully understood, distinct clinical features of the resulting tumors suggest involvement of disparate signaling mechanisms. When we compared the global phosphotyrosine proteomic profiles of isogenic colorectal cancer cell lines bearing either G12D or G13D KRASmutation, we observed both shared as well as unique signaling events induced by the two KRASmutations. Remarkably, while the G12D mutation led to an increase in membrane proximal and adherens junction signaling, the G13D mutation led to activation of signaling molecules such as nonreceptor tyrosine kinases, MAPK kinases, and regulators of metabolic processes. The importance of one of the cell surface molecules, MPZL1, which was found to be hyperphosphorylated in G12D cells, was confirmed by cellular assays as its knockdown led to a decrease in proliferation of G12D but not G13D expressing cells. Overall, our study reveals important signaling differences across two common KRASmutations and highlights the utility of our approach to systematically dissect subtle differences between related oncogenic mutants and potentially lead to individualized treatments.

Published
2021
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24. Proteogenomic Analysis of Candida glabrata using High Resolution Mass Spectrometry

Author

H. C. Harsha, Lakshmi Dhevi N. Selvan, Raju Ravikumar, Shivakumar Keerthikumar, Sneha M. Pinto, T. S. Keshava Prasad, Santosh Renuse, Yashwanth Subbannayya, Akhilesh Pandey, Nirujogi Raja Sekhar, Babylakshmi Muthusamy, Praveen Kumar, Raghothama Chaerkady, and Premendu P. Mathur

Subjects
Proteomics, Proteome, Resolution (mass spectrometry), Molecular Sequence Data, Codon, Initiator, Gene Expression, Candida glabrata, Biology, Tandem mass spectrometry, Peptide Mapping, Biochemistry, Genome, DNA sequencing, Fungal Proteins, Tandem Mass Spectrometry, Amino Acid Sequence, Gene, Genetics, Fourier Analysis, Reverse Transcriptase Polymerase Chain Reaction, Molecular Sequence Annotation, General Chemistry, Genome project, biology.organism_classification, Peptide Fragments, Energy and redox metabolism Mitochondrial medicine [NCMLS 4]
Abstract

Item does not contain fulltext Candida glabrata is a common opportunistic human pathogen leading to significant mortality in immunosuppressed and immunodeficient individuals. We carried out proteomic analysis of C. glabrata using high resolution Fourier transform mass spectrometry with MS resolution of 60,000 and MS/MS resolution of 7500. On the basis of 32,453 unique peptides identified from 118,815 peptide-spectrum matches, we validated 4421 of the 5283 predicted protein-coding genes (83%) in the C. glabrata genome. Further, searching the tandem mass spectra against a six frame translated genome database of C. glabrata resulted in identification of 11 novel protein coding genes and correction of gene boundaries for 14 predicted gene models. A subset of novel protein-coding genes and corrected gene models were validated at the transcript level by RT-PCR and sequencing. Our study illustrates how proteogenomic analysis enabled by high resolution mass spectrometry can enrich genome annotation and should be an integral part of ongoing genome sequencing and annotation efforts.

Published
2011
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25. A proteogenomic analysis of Anopheles gambiae using high-resolution Fourier transform mass spectrometry

Author

Raghothama Chaerkady, T. S. Keshava Prasad, Santosh Renuse, Godfree Mlambo, Sutopa B. Dwivedi, Sneha M. Pinto, Nandini A. Sahasrabuddhe, Harsh Pawar, Bernard Delanghe, Ajeet Kumar Mohanty, Yi Yang, Kumaran Kandasamy, Nirujogi Raja Sekhar, Akhilesh Pandey, Min-Sik Kim, Aditya P Dash, Rakesh Sharma, Derese Getnet, Ashwani Kumar, Jun Zhong, Babylakshmi Muthusamy, Mobolaji Okulate, Nirbhay Kumar, Robert M. MacCallum, and Dhanashree S. Kelkar

Subjects
Proteomics, Gene prediction, Molecular Sequence Data, Codon, Initiator, Sequence assembly, Genes, Insect, Biology, Genome, Mass Spectrometry, Open Reading Frames, Untranslated Regions, Anopheles, Genetics, Animals, Coding region, Gene, Genetics (clinical), Whole genome sequencing, Research, Chromosome Mapping, Reproducibility of Results, Molecular Sequence Annotation, Exons, Genomics, Genome project, Gene Annotation, Introns, Alternative Splicing, RNA Splice Sites, Peptides
Abstract

Anopheles gambiae is a major vector for malaria, which is a main public health burden in many parts of the world. The first draft of the An. gambiae genome sequence was released in 2002 containing ∼278 Mb (Holt et al. 2002). Mongin et al. (2004) discussed the limitations associated with this genome assembly. A gene set annotated by VectorBase contains both manually annotated genes and predicted gene models from GeneWise (Birney et al. 2004), ClusterMerge (Eyras et al. 2004), and SNAP (Li et al. 2007) algorithms. The VectorBase bioinformatic resource provides several annotated and curated vector genomes in a Web-accessible integrated format including DNA and protein alignments (Lawson et al. 2009). Based on manual appraisal, the VectorBase (http://agambiae.VectorBase.org) updated the Anopheles gambiae genebuild (AgamP3.5) in September 2009, which contained 12,604 protein-coding genes. The updated gene sets include 765 novel genes, modification of 3726 gene models, and deletion of 456 genes. The latest genebuild, AgamP3.6, was released in December 2010, which contains 12,669 protein-coding genes. This release includes 227 new genes, changes to the structure of 443 gene models, and deletion of three genes as compared to the AgamP3.5 genebuild. In the VectorBase–Ensembl genome annotation pipeline, genes are annotated based on mRNA/cDNA sequences and comparative proteomic evidence, as well as manual appraisal. Manually annotated gene models are given the highest preference followed by comparative gene models, EST-based models, and ab initio gene models. GeneWise-based prediction uses alignment of dipterans and other protein sequences to the An. gambiae genome for building gene models. The ClusterMerge algorithm builds models based on EST evidence (Eyras et al. 2004). The SNAP and Genscan algorithms were used to predict ab initio models that are also included in the current genebuild (Korf 2004). In the present study, we present many novel findings that were missed in spite of a robust annotation strategy and multiple revisions of An. gambiae genome annotations. The reverse process of genome annotation, i.e., from proteins to the genome, holds great promise for increasing the accuracy of the predicted gene structures. Annotation of genomes using mass spectrometry–based proteomics data is complementary to other gene prediction methods. Direct evidence for the protein-coding potential of the genome sequence can be obtained by searching tandem mass spectrometry data against nucleotide sequences like ESTs or genome sequence databases as against known protein databases (Pandey and Lewitter 1999; Pandey and Mann 2000; Choudhary et al. 2001; Mann and Pandey 2001; Xia et al. 2008). Certain features of peptides can provide definitive evidence pertaining to protein architecture that cannot be obtained from genome or transcript sequencing, e.g., acetylation of N termini of peptides, which indicates proximity to the translation start sites. An important outcome of such analyses is the identification of novel genes that have been entirely missed by other approaches. Protein-coding genes leading to splice variants, truncated proteins, and cSNPs can all also be directly studied by protein sequencing. Several studies have demonstrated the use of mass spectrometry–based proteomic approaches to validate or correct gene annotations in Homo sapiens (Molina et al. 2005; Suzuki and Sugano 2006; Sevinsky et al. 2008; Menon et al. 2009), Caenorhabditis elegans (Merrihew et al. 2008), Drosophila melanogaster (Brunner et al. 2007; Tress et al. 2008), An. gambiae (Pandey and Mann 2000; Kalume et al. 2005a,b; Okulate et al. 2007), Toxoplasma gondii (Xia et al. 2008), and Arabidopsis thaliana (Kuster et al. 2001; Baerenfaller et al. 2008). Here, we present the results of an extensive qualitative proteomic analysis of An. gambiae to better understand gene structures and their functions. We report validation of existing genes, correction of existing gene models, identification of novel genes, identification of novel splice variants, confirmation of splice sites, and assignment of translational start sites based on high-resolution mass spectrometry–derived data. A total of 2682 peptides were identified that could not be mapped onto existing VectorBase annotations. We also used gene prediction models by SNAP, and in some cases by Fgenesh and GenMark, which supported the peptide evidence to identify novel genes or alternate gene models. Finally, we performed RT-PCR and sequencing to support the existence of a number of novel and modified coding regions identified in this study.

Published
2011
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30. Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

Author

Prasad, T.S. Keshava, primary, Mohanty, Ajeet Kumar, additional, Kumar, Manish, additional, Sreenivasamurthy, Sreelakshmi K., additional, Dey, Gourav, additional, Nirujogi, Raja Sekhar, additional, Pinto, Sneha M., additional, Madugundu, Anil K., additional, Patil, Arun H., additional, Advani, Jayshree, additional, Manda, Srikanth S., additional, Gupta, Manoj Kumar, additional, Dwivedi, Sutopa B., additional, Kelkar, Dhanashree S., additional, Hall, Brantley, additional, Jiang, Xiaofang, additional, Peery, Ashley, additional, Rajagopalan, Pavithra, additional, Yelamanchi, Soujanya D., additional, Solanki, Hitendra S., additional, Raja, Remya, additional, Sathe, Gajanan J., additional, Chavan, Sandip, additional, Verma, Renu, additional, Patel, Krishna M., additional, Jain, Ankit P., additional, Syed, Nazia, additional, Datta, Keshava K., additional, Khan, Aafaque Ahmed, additional, Dammalli, Manjunath, additional, Jayaram, Savita, additional, Radhakrishnan, Aneesha, additional, Mitchell, Christopher J., additional, Na, Chan-Hyun, additional, Kumar, Nirbhay, additional, Sinnis, Photini, additional, Sharakhov, Igor V., additional, Wang, Charles, additional, Gowda, Harsha, additional, Tu, Zhijian, additional, Kumar, Ashwani, additional, and Pandey, Akhilesh, additional

Published
2016
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31. A Comprehensive Proteomics Analysis of the Human Iris Tissue: Ready to Embrace Postgenomics Precision Medicine in Ophthalmology?

Author

Murthy, Krishna R., primary, Dammalli, Manjunath, additional, Pinto, Sneha M., additional, Murthy, Kalpana Babu, additional, Nirujogi, Raja Sekhar, additional, Madugundu, Anil K., additional, Dey, Gourav, additional, Subbannayya, Yashwanth, additional, Mishra, Uttam Kumar, additional, Nair, Bipin, additional, Gowda, Harsha, additional, and Prasad, T.S. Keshava, additional

Published
2016
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32. Phosphotyrosine profiling of curcumin-induced signaling

Author

Sathe, Gajanan, primary, Pinto, Sneha M., additional, Syed, Nazia, additional, Nanjappa, Vishalakshi, additional, Solanki, Hitendra S., additional, Renuse, Santosh, additional, Chavan, Sandip, additional, Khan, Aafaque Ahmad, additional, Patil, Arun H., additional, Nirujogi, Raja Sekhar, additional, Nair, Bipin, additional, Mathur, Premendu Prakash, additional, Prasad, T. S. Keshava, additional, Gowda, Harsha, additional, and Chatterjee, Aditi, additional

Published
2016
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33. Dysregulation of splicing proteins in head and neck squamous cell carcinoma

Author

Radhakrishnan, Aneesha, primary, Nanjappa, Vishalakshi, additional, Raja, Remya, additional, Sathe, Gajanan, additional, Chavan, Sandip, additional, Nirujogi, Raja Sekhar, additional, Patil, Arun H., additional, Solanki, Hitendra, additional, Renuse, Santosh, additional, Sahasrabuddhe, Nandini A., additional, Mathur, Premendu P., additional, Prasad, T. S. Keshava, additional, Kumar, Prashant, additional, Califano, Joseph A., additional, Sidransky, David, additional, Pandey, Akhilesh, additional, Gowda, Harsha, additional, and Chatterjee, Aditi, additional

Published
2016
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34. A multi-omic analysis of human naïve CD4+ T cells

Author

10722811, 30439244, Mitchell, Christopher J., Getnet, Derese, Kim, Min Sik, Manda, Srikanth S., Kumar, Praveen, Huang, Tai Chung, Pinto, Sneha M., Nirujogi, Raja Sekhar, Iwasaki, Mio, Shaw, Patrick G., Wu, Xinyan, Zhong, Jun, Chaerkady, Raghothama, Marimuthu, Arivusudar, Muthusamy, Babylakshmi, Sahasrabuddhe, Nandini A., Raju, Rajesh, Bowman, Caitlyn, Danilova, Ludmila, Cutler, Jevon, Kelkar, Dhanashree S., Drake, Charles G., Prasad, T. S Keshava, Marchionni, Luigi, Murakami, Peter N., Scott, Alan F., Shi, Leming, Thierry-Mieg, Jean, Thierry-Mieg, Danielle, Irizarry, Rafael, Cope, Leslie, Ishihama, Yasushi, Wang, Charles, Gowda, Harsha, Pandey, Akhilesh, 10722811, 30439244, Mitchell, Christopher J., Getnet, Derese, Kim, Min Sik, Manda, Srikanth S., Kumar, Praveen, Huang, Tai Chung, Pinto, Sneha M., Nirujogi, Raja Sekhar, Iwasaki, Mio, Shaw, Patrick G., Wu, Xinyan, Zhong, Jun, Chaerkady, Raghothama, Marimuthu, Arivusudar, Muthusamy, Babylakshmi, Sahasrabuddhe, Nandini A., Raju, Rajesh, Bowman, Caitlyn, Danilova, Ludmila, Cutler, Jevon, Kelkar, Dhanashree S., Drake, Charles G., Prasad, T. S Keshava, Marchionni, Luigi, Murakami, Peter N., Scott, Alan F., Shi, Leming, Thierry-Mieg, Jean, Thierry-Mieg, Danielle, Irizarry, Rafael, Cope, Leslie, Ishihama, Yasushi, Wang, Charles, Gowda, Harsha, and Pandey, Akhilesh

Abstract

Background: Cellular function and diversity are orchestrated by complex interactions of fundamental biomolecules including DNA, RNA and proteins. Technological advances in genomics, epigenomics, transcriptomics and proteomics have enabled massively parallel and unbiased measurements. Such high-throughput technologies have been extensively used to carry out broad, unbiased studies, particularly in the context of human diseases. Nevertheless, a unified analysis of the genome, epigenome, transcriptome and proteome of a single human cell type to obtain a coherent view of the complex interplay between various biomolecules has not yet been undertaken. Here, we report the first multi-omic analysis of human primary naïve CD4+ T cells isolated from a single individual. Results: Integrating multi-omics datasets allowed us to investigate genome-wide methylation and its effect on mRNA/protein expression patterns, extent of RNA editing under normal physiological conditions and allele specific expression in naïve CD4+ T cells. In addition, we carried out a multi-omic comparative analysis of naïve with primary resting memory CD4+ T cells to identify molecular changes underlying T cell differentiation. This analysis provided mechanistic insights into how several molecules involved in T cell receptor signaling are regulated at the DNA, RNA and protein levels. Phosphoproteomics revealed downstream signaling events that regulate these two cellular states. Availability of multi-omics data from an identical genetic background also allowed us to employ novel proteogenomics approaches to identify individual-specific variants and putative novel protein coding regions in the human genome. Conclusions: We utilized multiple high-throughput technologies to derive a comprehensive profile of two primary human cell types, naïve CD4+ T cells and memory CD4+ T cells, from a single donor. Through vertical as well as horizontal integration of whole genome sequencing, methylation arrays, RNA-Seq, miRN

Published
2015

35. SILAC-based quantitative proteomic analysis of gastric cancer secretome

Author

H. C. Harsha, Sneha M. Pinto, Hassan Ashktorab, Duane T. Smoot, Teesta V. Katte, Jagadeesha Maharudraiah, Girija Ramaswamy, Rekha V. Kumar, Nirujogi Raja Sekhar, T. S. Keshava Prasad, Manoj Kumar Kashyap, S Srikanth, Yulan Cheng, Yashwanth Subbannayya, Lavanya Balakrishnan, Nandini A. Sahasrabuddhe, Stephen J. Meltzer, Praveen Kumar, Aditi Chatterjee, Akhilesh Pandey, Juan Carlos Roa, Harsh Pawar, Arivusudar Marimuthu, Raghothama Chaerkady, and Nazia Syed

Subjects
Proteomics, Screening test, Clinical Biochemistry, Early detection, Tumor cells, Gastric carcinoma, Biology, Adenocarcinoma, Bioinformatics, Article, Mass Spectrometry, Causes of cancer, Stomach Neoplasms, Stable isotope labeling by amino acids in cell culture, Cell Line, Tumor, medicine, Biomarkers, Tumor, Humans, Amino Acids, Chromatography, High Pressure Liquid, Serine Endopeptidases, Cancer, Computational Biology, Membrane Transport Proteins, Proteins, medicine.disease, Immunohistochemistry, Mannose-Binding Lectins, Isotope Labeling, Cancer research, Intercellular Signaling Peptides and Proteins, Electrophoresis, Polyacrylamide Gel, Proprotein Convertases, Proprotein Convertase 9
Abstract

Gastric cancer is a commonly occurring cancer in Asia and one of the leading causes of cancer deaths. However, there is no reliable blood-based screening test for this cancer. Identifying proteins secreted from tumor cells could lead to the discovery of clinically useful biomarkers for early detection of gastric cancer.A SILAC-based quantitative proteomic approach was employed to identify secreted proteins that were differentially expressed between neoplastic and non-neoplastic gastric epithelial cells. Proteins from the secretome were subjected to SDS-PAGE and SCX-based fractionation, followed by mass spectrometric analysis on an LTQ-Orbitrap Velos mass spectrometer. Immunohistochemical labeling was employed to validate a subset of candidates using tissue microarrays.We identified 2205 proteins in the gastric cancer secretome of which 263 proteins were overexpressed greater than fourfold in gastric cancer-derived cell lines as compared to non-neoplastic gastric epithelial cells. Three candidate proteins, proprotein convertase subtilisin/kexin type 9 (PCSK9), lectin mannose binding 2 (LMAN2), and PDGFA-associated protein 1 (PDAP1) were validated by immunohistochemical labeling.We report here the largest cancer secretome described to date. The novel biomarkers identified in the current study are excellent candidates for further testing as early detection biomarkers for gastric adenocarcinoma.

Published
2013

36. Identification of long-lived synaptic proteins by proteomic analysis of synaptosome protein turnover.

Author

Seok Heo, Diering, Graham H., Chan Hyun Na, Nirujogi, Raja Sekhar, Bachman, Julia L., Pandey, Akhilesh, and Huganir, Richard L.

Subjects
PROTEOMICS, SYNAPTOSOMES, MEMORY, CYTOSOL, LABORATORY mice
Abstract

Memory formation is believed to result from changes in synapse strength and structure. While memories may persist for the lifetime of an organism, the proteins and lipids that make up synapses undergo constant turnover with lifetimes from minutes to days. The molecular basis for memory maintenance may rely on a subset of long-lived proteins (LLPs). While it is known that LLPs exist, whether such proteins are present at synapses is unknown. We performed an unbiased screen using metabolic pulse-chase labeling in vivo in mice and in vitro in cultured neurons combined with quantitative proteomics. We identified synaptic LLPs with half-lives of several months or longer. Proteins in synaptic fractions generally exhibited longer lifetimes than proteins in cytosolic fractions. Protein turnover was sensitive to pharmacological manipulations of activity in neuronal cultures or in mice exposed to an enriched environment. We show that synapses contain LLPs that may underlie stabile long-lasting changes in synaptic structure and function. [ABSTRACT FROM AUTHOR]

Published
2018
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37. A proteogenomic approach to map the proteome of an unsequenced pathogen - Leishmania donovani

Author

Dhanashree S. Kelkar, Nandini A. Sahasrabuddhe, Akhilesh Pandey, H. C. Harsha, Milind S. Patole, Shivakumar Keerthikumar, Harshal B. Nemade, Harsh Pawar, Santosh Renuse, Raghothama Chaerkady, Sweta N. Khobragade, Abhilash K. Venugopal, Ghantasala S. Sameer Kumar, Nirujogi Raja Sekhar, Jyoti Sharma, Babylakshmi Muthusamy, and Kumaran Kandasamy

Subjects
Proteomics, Proteome, Virulence Factors, Molecular Sequence Data, Leishmania donovani, Protozoan Proteins, Biochemistry, Genome, Tandem Mass Spectrometry, parasitic diseases, medicine, Amino Acid Sequence, Amastigote, Databases, Protein, Molecular Biology, Whole genome sequencing, Genetics, biology, Proteomic Profiling, Leishmaniasis, medicine.disease, biology.organism_classification, Visceral leishmaniasis, Immunology, Leishmaniasis, Visceral, Energy and redox metabolism Mitochondrial medicine [NCMLS 4]
Abstract

Item does not contain fulltext 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 22,322 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. 01 maart 2012

Published
2012

38. Proteomic analysis of the abomasal mucosal response following infection by the nematode, Haemonchus contortus, in genetically resistant and susceptible sheep

Author

Antonio Reverter, Michelle L. Colgrave, Rakesh Sharma, Nicholas M. Andronicos, Moira Menzies, Peter W. Hunt, Aaron Ingham, H. C. Harsha, Nirujogi Raja Sekhar, Michael Lees, Shivashankar H. Nagaraj, and Akhilesh Pandey

Subjects
Proteomics, Proteome, 060109 Proteomics and Intermolecular Interactions (excl. Medical Proteomics), Biophysics, Biochemistry, Microbiology, Host-Parasite Interactions, Intestinal mucosa, Species Specificity, Haemonchus contortus, medicine, nematode infection, Parasite hosting, Animals, Genetic Predisposition to Disease, Intestinal Mucosa, education, 060408 Genomics, education.field_of_study, Sheep, biology, Trefoil factor 2, genetically susceptible sheep, proteomic analysis, medicine.disease, biology.organism_classification, genetically resistant sheep, 070708 Veterinary Parasitology, Nematode, Nematode infection, Immunology, abomasal mucosal response, 060406 Genetic Immunology, Haemonchus, Haemonchiasis, 070203 Animal Management, 070705 Veterinary Immunology
Abstract

Sheep have a variable ability to resist gastrointestinal nematode infection, but the key factors mediating this response are poorly defined. Here we report the first large-scale application of quantitative proteomic technologies to define proteins that are differentially abundant between sheep selectively bred to have an enhanced (resistant) or reduced (susceptible) ability to eliminate nematodes. Samples were collected from the abomasal mucosa three days after experimental challenge with the nematode, Haemonchus contortus. This timing reflects the initial interaction of host and parasite, and the tissue represents the immediate interface. We identified and quantified more than 4400 unique proteins, of which 158 proteins showed > 1.5 fold difference between the resistant and susceptible sheep. Trefoil factor 2, a member of RAS oncogene family (RAP1A) and ring finger protein 126 were amongst the proteins found to be highly abundant in the abomasal surface of resistant sheep, whereas adenosine deaminase and the gastrokine-3 like precursor were found at higher levels in susceptible sheep. Construction of gut proteome interaction networks identified mitochondrial function and energetic partitioning as important components of an effective nematode eliminating response. The differentially abundant proteins may be useful targets for phenotypic tests that aim to identify sheep with an enhanced ability to resist nematode infection.

Published
2011

39. Phosphoproteomic Profiling Reveals Epstein-Barr Virus Protein Kinase Integration of DNA Damage Response and Mitotic Signaling

Author

Li, Renfeng, primary, Liao, Gangling, additional, Nirujogi, Raja Sekhar, additional, Pinto, Sneha M., additional, Shaw, Patrick G., additional, Huang, Tai-Chung, additional, Wan, Jun, additional, Qian, Jiang, additional, Gowda, Harsha, additional, Wu, Xinyan, additional, Lv, Dong-Wen, additional, Zhang, Kun, additional, Manda, Srikanth S., additional, Pandey, Akhilesh, additional, and Hayward, S. Diane, additional

Published
2015
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41. A multi-omic analysis of human naïve CD4+ T cells

Author

Mitchell, Christopher J., primary, Getnet, Derese, additional, Kim, Min-Sik, additional, Manda, Srikanth S., additional, Kumar, Praveen, additional, Huang, Tai-Chung, additional, Pinto, Sneha M., additional, Nirujogi, Raja Sekhar, additional, Iwasaki, Mio, additional, Shaw, Patrick G., additional, Wu, Xinyan, additional, Zhong, Jun, additional, Chaerkady, Raghothama, additional, Marimuthu, Arivusudar, additional, Muthusamy, Babylakshmi, additional, Sahasrabuddhe, Nandini A., additional, Raju, Rajesh, additional, Bowman, Caitlyn, additional, Danilova, Ludmila, additional, Cutler, Jevon, additional, Kelkar, Dhanashree S., additional, Drake, Charles G., additional, Prasad, T. S. Keshava, additional, Marchionni, Luigi, additional, Murakami, Peter N., additional, Scott, Alan F., additional, Shi, Leming, additional, Thierry-Mieg, Jean, additional, Thierry-Mieg, Danielle, additional, Irizarry, Rafael, additional, Cope, Leslie, additional, Ishihama, Yasushi, additional, Wang, Charles, additional, Gowda, Harsha, additional, and Pandey, Akhilesh, additional

Published
2015
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42. Phosphoproteomic profiling of tumor tissues identifies HSP27 Ser82 phosphorylation as a robust marker of early ischemia

Author

Zahari, Muhammad Saddiq, primary, Wu, Xinyan, additional, Pinto, Sneha M., additional, Nirujogi, Raja Sekhar, additional, Kim, Min-Sik, additional, Fetics, Barry, additional, Philip, Mathew, additional, Barnes, Sheri R., additional, Godfrey, Beverly, additional, Gabrielson, Edward, additional, Nevo, Erez, additional, and Pandey, Akhilesh, additional

Published
2015
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43. Proteomics of Human Aqueous Humor

Author

Murthy, Krishna R., primary, Rajagopalan, Pavithra, additional, Pinto, Sneha M., additional, Advani, Jayshree, additional, Murthy, Praveen R., additional, Goel, Renu, additional, Subbannayya, Yashwanth, additional, Balakrishnan, Lavanya, additional, Dash, Mahashweta, additional, Anil, Abhijith K., additional, Manda, Srikanth S., additional, Nirujogi, Raja Sekhar, additional, Kelkar, Dhanashree S., additional, Sathe, Gajanan J., additional, Dey, Gourav, additional, Chatterjee, Aditi, additional, Gowda, Harsha, additional, Chakravarti, Shukti, additional, Shankar, Subramanian, additional, Sahasrabuddhe, Nandini A., additional, Nair, Bipin, additional, Somani, Babu Lal, additional, Prasad, T. S. Keshava, additional, and Pandey, Akhilesh, additional

Published
2015
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44. Phosphotyrosine profiling identifies ephrin receptor A2 as a potential therapeutic target in esophageal squamous‐cell carcinoma

Author

Syed, Nazia, primary, Barbhuiya, Mustafa A., additional, Pinto, Sneha M., additional, Nirujogi, Raja Sekhar, additional, Renuse, Santosh, additional, Datta, Keshava K., additional, Khan, Aafaque Ahmad, additional, Srikumar, Kotteazeth, additional, Prasad, T. S. Keshava, additional, Kumar, M. Vijaya, additional, Kumar, Rekha Vijay, additional, Chatterjee, Aditi, additional, Pandey, Akhilesh, additional, and Gowda, Harsha, additional

Published
2015
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45. Phosphoproteomic analysis reveals compensatory effects in the piriform cortex of VX nerve agent exposed rats

Author

Nirujogi, Raja Sekhar, primary, Wright, James D., additional, Manda, Srikanth S., additional, Zhong, Jun, additional, Na, Chan Hyun, additional, Meyerhoff, James, additional, Benton, Bernard, additional, Jabbour, Rabih, additional, Willis, Kristen, additional, Kim, Min-Sik, additional, Pandey, Akhilesh, additional, and Sekowski, Jennifer W., additional

Published
2015
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46. Quantitative phosphoproteomic analysis of IL-33-mediated signaling

Author

Pinto, Sneha M., primary, Nirujogi, Raja Sekhar, additional, Rojas, Pamela Leal, additional, Patil, Arun H., additional, Manda, Srikanth S., additional, Subbannayya, Yashwanth, additional, Roa, Juan Carlos, additional, Chatterjee, Aditi, additional, Prasad, T. S. Keshava, additional, and Pandey, Akhilesh, additional

Published
2015
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47. A draft map of the human proteome

Author

Kim, Minsik, Pinto, Sneha Maria Aria, Getnet, Derese, Nirujogi, Raja Sekhar Ekhar, Manda, Srikanth Srinivas Rinivas, Chaerkady, Raghothama, Madugundu, Anil Kumar, Kelkar, Dhanashree, Isserlin, Ruth, Jain, Shobhit, Thomas, Joji Kurian, Muthusamy, Babylakshmi, Leal-Rojas, Pamela, Kumar, Praveen, Sahasrabuddhe, Nandini, Balakrishnan, Lavanya, Advani, Jayshree, George, Bijesh, Renuse, Santosh, Selvan, Lakshmi Dhevi Nagarajha Nagarajha, Patil, Arun, Nanjappa, Vishalakshi, Radhakrishnan, Aneesha, Prasad, Samarjeet, Subbannayya, Tejaswini, Raju, Rajesh, Kumar, Manish Vijaya, Sreenivasamurthy, Sreelakshmi, Marimuthu, Arivusudar, Sathe, Gajanan, Chavan, Sandip, Datta, Keshava, Subbannayya, Yashwanth, Sahu, Apeksha, Yelamanchi, Soujanya, Jayaram, Savita, Rajagopalan, Pavithra, Sharma, Jyoti, Murthy, Krishna Ramachandra, Syed, Nazia, Goel, Renu, Khan, Aafaqueahmad, Ahmad, Sartaj Akhtar, Dey, Gourav, Mudgal, Keshav, Chatterjee, Aditi, Huang, Taichung, Zhong, Jun, Wu, Xinyan, Shaw, Patrick, Freed, Donald, Zahari, Muhammad Saddiq, Mukherjee, Kanchan Kumar, Shankar, Subramanian Ravi, Mahadevan, Anita, Lam, Henry H N, Mitchell, Christopher, Shankar, Susarla Krishna Rishna, Satishchandra, Parthasarathy, Schroeder, John, Sirdeshmukh, Ravi, Maitra, Anirban, Leach, Steven, Drake, Charles, Halushka, Marc Kenneth, Prasad, Thottethodi Subrahmanya Keshava, Hruban, Ralph, Kerr, Candace, Bader, Gary, Iacobuzio-Donahue, Christine, Gowda, Harsha, Pandey, Akhilesh, Kim, Minsik, Pinto, Sneha Maria Aria, Getnet, Derese, Nirujogi, Raja Sekhar Ekhar, Manda, Srikanth Srinivas Rinivas, Chaerkady, Raghothama, Madugundu, Anil Kumar, Kelkar, Dhanashree, Isserlin, Ruth, Jain, Shobhit, Thomas, Joji Kurian, Muthusamy, Babylakshmi, Leal-Rojas, Pamela, Kumar, Praveen, Sahasrabuddhe, Nandini, Balakrishnan, Lavanya, Advani, Jayshree, George, Bijesh, Renuse, Santosh, Selvan, Lakshmi Dhevi Nagarajha Nagarajha, Patil, Arun, Nanjappa, Vishalakshi, Radhakrishnan, Aneesha, Prasad, Samarjeet, Subbannayya, Tejaswini, Raju, Rajesh, Kumar, Manish Vijaya, Sreenivasamurthy, Sreelakshmi, Marimuthu, Arivusudar, Sathe, Gajanan, Chavan, Sandip, Datta, Keshava, Subbannayya, Yashwanth, Sahu, Apeksha, Yelamanchi, Soujanya, Jayaram, Savita, Rajagopalan, Pavithra, Sharma, Jyoti, Murthy, Krishna Ramachandra, Syed, Nazia, Goel, Renu, Khan, Aafaqueahmad, Ahmad, Sartaj Akhtar, Dey, Gourav, Mudgal, Keshav, Chatterjee, Aditi, Huang, Taichung, Zhong, Jun, Wu, Xinyan, Shaw, Patrick, Freed, Donald, Zahari, Muhammad Saddiq, Mukherjee, Kanchan Kumar, Shankar, Subramanian Ravi, Mahadevan, Anita, Lam, Henry H N, Mitchell, Christopher, Shankar, Susarla Krishna Rishna, Satishchandra, Parthasarathy, Schroeder, John, Sirdeshmukh, Ravi, Maitra, Anirban, Leach, Steven, Drake, Charles, Halushka, Marc Kenneth, Prasad, Thottethodi Subrahmanya Keshava, Hruban, Ralph, Kerr, Candace, Bader, Gary, Iacobuzio-Donahue, Christine, Gowda, Harsha, and Pandey, Akhilesh

Abstract

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. © 2014 Macmillan Publishers Limited.

Published
2014

48. Brain Proteomics of Anopheles gambiae

Author

Dwivedi, Sutopa B., primary, Muthusamy, Babylakshmi, additional, Kumar, Praveen, additional, Kim, Min-Sik, additional, Nirujogi, Raja Sekhar, additional, Getnet, Derese, additional, Ahiakonu, Priscilla, additional, De, Gourav, additional, Nair, Bipin, additional, Gowda, Harsha, additional, Prasad, T.S. Keshava, additional, Kumar, Nirbhay, additional, Pandey, Akhilesh, additional, and Okulate, Mobolaji, additional

Published
2014
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49. Identification and Characterization of Proteins Encoded by Chromosome 12 as Part of Chromosome-centric Human Proteome Project

Author

Manda, Srikanth Srinivas, primary, Nirujogi, Raja Sekhar, additional, Pinto, Sneha Maria, additional, Kim, Min-Sik, additional, Datta, Keshava K., additional, Sirdeshmukh, Ravi, additional, Prasad, T. S. Keshava, additional, Thongboonkerd, Visith, additional, Pandey, Akhilesh, additional, and Gowda, Harsha, additional

Published
2014
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50. Proteomic analysis of human osteoarthritis synovial fluid

Author

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

Published
2014
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