1
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Sambath J, Noronha V, Manda SS, Mishra R, Chandrani P, Patil V, Menon N, Chougule A, Ramachandran V, Limaye S, Kuriakose MA, Banavali SD, Kumar P, Prabhash K. Whole exome sequencing uncovers HRAS mutations as potential mediators of resistance to metronomic chemotherapy. Gene 2024; 893:147952. [PMID: 37918550 DOI: 10.1016/j.gene.2023.147952] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Revised: 10/11/2023] [Accepted: 10/30/2023] [Indexed: 11/04/2023]
Abstract
OBJECTIVES The aim of this pilot study is to identify the genetic factors that contribute to the response of metronomic chemotherapy in head and neck squamous cell carcinoma (HNSCC) patients using whole-exome sequencing (WES). This study would facilitate the identification of predictive biomarkers, which would enable personalized treatment strategies and improve treatment outcomes for patients with HNSCC. MATERIALS AND METHODS We have selected patients with recurrent head and neck cancer who underwent metronomic chemotherapy. Sequential tumor biopsies were collected from the patients at different stages of treatment to capture the genomic alterations and tumor evolution during metronomic chemotherapy and sequenced using WES. RESULTS We identified several known HNSCC hallmark genes reported in COSMIC, including KMT2B, NOTCH1, FAT1, TP53, HRAS, CASP8, and CDKN2A. Copy number alteration analysis revealed amplifications and deletions in several oncogenic and tumor suppressor genes. COSMIC Mutational Signature 15 associated with defective DNA mismatch repair was enriched in 73% of HNSCC samples. Further, the comparison of genomic alterations between responders and non-responders identified HRAS gene uniquely mutated in non-responders that could potentially contribute to resistance against metronomic chemotherapy. DISCUSSION Our findings corroborate the molecular heterogeneity of recurrent HNSCC tumors and establish an association between HRAS mutations and resistance to metronomic chemotherapy, suggesting HRAS as a potential therapeutic target. Combining HRAS inhibitors with metronomic regimens could improve treatment sensitivity in HRAS-mutated HNSCC patients. Further studies are needed to fully elucidate the genomic mechanisms underlying the response to metronomic chemotherapy.
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Affiliation(s)
- Janani Sambath
- Institute of Bioinformatics, Bangalore, India; Manipal Academy of Higher Education (MAHE), Manipal, India
| | | | - Srikanth S Manda
- Karkinos Foundation, Mumbai, India; Karkinos Healthcare Pvt Ltd., Mumbai, India
| | | | | | | | | | | | | | - Sewanti Limaye
- Division of Medical and Precision Oncology, Sir H.N. Reliance Foundation Hospital and Research Centre, Mumbai, India
| | - Moni A Kuriakose
- Karkinos Foundation, Mumbai, India; Karkinos Healthcare Pvt Ltd., Mumbai, India
| | | | - Prashant Kumar
- Karkinos Foundation, Mumbai, India; Karkinos Healthcare Pvt Ltd., Mumbai, India.
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2
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Gonçalves E, Poulos RC, Cai Z, Barthorpe S, Manda SS, Lucas N, Beck A, Bucio-Noble D, Dausmann M, Hall C, Hecker M, Koh J, Lightfoot H, Mahboob S, Mali I, Morris J, Richardson L, Seneviratne AJ, Shepherd R, Sykes E, Thomas F, Valentini S, Williams SG, Wu Y, Xavier D, MacKenzie KL, Hains PG, Tully B, Robinson PJ, Zhong Q, Garnett MJ, Reddel RR. Pan-cancer proteomic map of 949 human cell lines. Cancer Cell 2022; 40:835-849.e8. [PMID: 35839778 PMCID: PMC9387775 DOI: 10.1016/j.ccell.2022.06.010] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/29/2022] [Accepted: 06/21/2022] [Indexed: 12/12/2022]
Abstract
The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.
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Affiliation(s)
- Emanuel Gonçalves
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK; Instituto Superior Técnico (IST), Universidade de Lisboa, 1049-001 Lisboa, Portugal; INESC-ID, 1000-029 Lisboa, Portugal
| | - Rebecca C Poulos
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Zhaoxiang Cai
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Syd Barthorpe
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Srikanth S Manda
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Natasha Lucas
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Alexandra Beck
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Daniel Bucio-Noble
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Michael Dausmann
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Caitlin Hall
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Michael Hecker
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Jennifer Koh
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Howard Lightfoot
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Sadia Mahboob
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Iman Mali
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - James Morris
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Laura Richardson
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Akila J Seneviratne
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Rebecca Shepherd
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Erin Sykes
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Frances Thomas
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Sara Valentini
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Steven G Williams
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Yangxiu Wu
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Dylan Xavier
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Karen L MacKenzie
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Peter G Hains
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Brett Tully
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Phillip J Robinson
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
| | - Qing Zhong
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
| | - Mathew J Garnett
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK.
| | - Roger R Reddel
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
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3
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Abstract
Data-independent-acquisition mass spectrometry (DIA-MS) is a state-of-the-art proteomic technique for high-throughput identification and quantification of peptides and proteins. Interpretation of DIA-MS data relies on the use of a spectral library, which is optimally created from data acquired from the same samples in data-dependent acquisition (DDA) mode. As DIA-MS quantification relies on the spectral libraries, having a high-quality, non-redundant, and comprehensive spectral library is essential. This article describes the major steps for creating a high-quality spectral library using a combination of multiple complementary search engines. We discuss appropriate strategies to control the false discovery rate for the final spectral library as a result of merging multiple searches. © 2021 The Authors Current Protocols © 2021 Wiley Periodicals LLC. Basic Protocol 1: Searching DDA-MS files with multiple search engines Basic Protocol 2: Merging results from multiple search engines Basic Protocol 3: Creating spectral libraries from merged results Alternate Protocol: Using CLI for automating tasks Support Protocol: Creating concatenated FASTA files.
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Affiliation(s)
- Srikanth S Manda
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Zainab Noor
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Peter G Hains
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Qing Zhong
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
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4
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Poulos RC, Hains PG, Shah R, Lucas N, Xavier D, Manda SS, Anees A, Koh JMS, Mahboob S, Wittman M, Williams SG, Sykes EK, Hecker M, Dausmann M, Wouters MA, Ashman K, Yang J, Wild PJ, deFazio A, Balleine RL, Tully B, Aebersold R, Speed TP, Liu Y, Reddel RR, Robinson PJ, Zhong Q. Strategies to enable large-scale proteomics for reproducible research. Nat Commun 2020; 11:3793. [PMID: 32732981 PMCID: PMC7393074 DOI: 10.1038/s41467-020-17641-3] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 07/08/2020] [Indexed: 01/12/2023] Open
Abstract
Reproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy. We perform 1560 data independent acquisition (DIA)-MS runs of eight samples containing known proportions of ovarian and prostate cancer tissue and yeast, or control HEK293T cells. Replicates are run on six mass spectrometers operating continuously with varying maintenance schedules over four months, interspersed with ~5000 other runs. We utilise negative controls and replicates to remove unwanted variation and enhance biological signal, outperforming existing methods. We also design a method for reducing missing values. Integrating these computational modules into a pipeline (ProNorM), we mitigate variation among instruments over time and accurately predict tissue proportions. We demonstrate how to improve the quantitative analysis of large-scale DIA-MS data, providing a pathway toward clinical proteomics. Clinical proteomics critically depends on the ability to acquire highly reproducible data over an extended period of time. Here, the authors assess reproducibility over four months across different mass spectrometers and develop a computational approach to mitigate variation among instruments over time.
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Affiliation(s)
- Rebecca C Poulos
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Peter G Hains
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Rohan Shah
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Natasha Lucas
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Dylan Xavier
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Srikanth S Manda
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Asim Anees
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Jennifer M S Koh
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Sadia Mahboob
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Max Wittman
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Steven G Williams
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Erin K Sykes
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Michael Hecker
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Michael Dausmann
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Merridee A Wouters
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | | | - Jean Yang
- School of Mathematics and Statistics, The University of Sydney, Sydney, Australia
| | - Peter J Wild
- Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany.,Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Anna deFazio
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW, Australia.,Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.,Department of Gynaecological Oncology, Westmead Hospital, Westmead, NSW, Australia
| | - Rosemary L Balleine
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Brett Tully
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.,Faculty of Science, University of Zürich, Zürich, Switzerland
| | - Terence P Speed
- Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.,Department of Mathematics and Statistics, University of Melbourne, Melbourne, VIC, Australia
| | - Yansheng Liu
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, USA.,Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
| | - Roger R Reddel
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Phillip J Robinson
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Qing Zhong
- ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
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5
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Logan J, Pearson MS, Manda SS, Choi YJ, Field M, Eichenberger RM, Mulvenna J, Nagaraj SH, Fujiwara RT, Gazzinelli-Guimaraes P, Bueno L, Mati V, Bethony JM, Mitreva M, Sotillo J, Loukas A. Comprehensive analysis of the secreted proteome of adult Necator americanus hookworms. PLoS Negl Trop Dis 2020; 14:e0008237. [PMID: 32453752 PMCID: PMC7274458 DOI: 10.1371/journal.pntd.0008237] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Revised: 06/05/2020] [Accepted: 03/18/2020] [Indexed: 12/22/2022] Open
Abstract
The human hookworm Necator americanus infects more than 400 million people worldwide, contributing substantially to the poverty in these regions. Adult stage N. americanus live in the small intestine of the human host where they inject excretory/secretory (ES) products into the mucosa. ES products have been characterized at the proteome level for a number of animal hookworm species, but until now, the difficulty in obtaining sufficient live N. americanus has been an obstacle in characterizing the secretome of this important human pathogen. Herein we describe the ES proteome of N. americanus and utilize this information along with RNA Seq data to conduct the first proteogenomic analysis of a parasitic helminth, significantly improving the available genome and thereby generating a robust description of the parasite secretome. The genome annotation resulted in a revised prediction of 3,425 fewer genes than initially reported, accompanied by a significant increase in the number of exons and introns, total gene length and the percentage of the genome covered by genes. Almost 200 ES proteins were identified by LC-MS/MS with SCP/TAPS proteins, ‘hypothetical’ proteins and proteases among the most abundant families. These proteins were compared to commonly used model species of human parasitic infections, including Ancylostoma caninum, Nippostrongylus brasiliensis and Heligmosomoides polygyrus. SCP/TAPS proteins are immunogenic in nematode infections, so we expressed four of those identified in this study in recombinant form and showed that they are all recognized to varying degrees by serum antibodies from hookworm-infected subjects from a disease-endemic area of Brazil. Our findings provide valuable information on important families of proteins with both known and unknown functions that could be instrumental in host-parasite interactions, including protein families that might be key for parasite survival in the onslaught of robust immune responses, as well as vaccine and diagnostic targets. Hookworms infect hundreds of millions of people in tropical regions of the world. Adult worms reside in the small bowel where they feed on blood, causing iron-deficiency anemia when present in large numbers and contributing substantially to the poverty in these regions. Hookworms inject excretory/secretory (ES) products into the gut tissue when they feed, and while the protein constituents of ES products have been characterized for a number of animal hookworm species, difficulty in obtaining sufficient live human hookworms has thus far precluded characterization of the secreted proteome. Herein we describe the ES proteins of the major human hookworm, Necator americanus, and utilize this information to significantly improve the available genome sequence. Almost 200 ES proteins were identified and compared to the secreted proteomes of other parasitic roundworms to provide a molecular snapshot of the host-parasite interface. We produced recombinant forms of some of the identified proteins and showed that they are all recognized to varying degrees by antibodies from hookworm-infected subjects. Our work sheds light on important families of proteins that might be key for parasite survival in the human host, and presents a dataset that can now be mined in the search for vaccine, drug and diagnostic targets.
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Affiliation(s)
- Jayden Logan
- Centre for Molecular Therapeutics, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia
| | - Mark S. Pearson
- Centre for Molecular Therapeutics, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia
| | - Srikanth S. Manda
- Cancer Data Science Group, ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW, Australia
- LifeBytes India Pvt Ltd, Whitefield, Bangalore, India
| | - Young-Jun Choi
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Matthew Field
- Centre for Molecular Therapeutics, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia
| | - Ramon M. Eichenberger
- Centre for Molecular Therapeutics, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia
| | - Jason Mulvenna
- QIMR-Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Shivashankar H. Nagaraj
- Institute of Health and Biomedical Innovation and Translational Research Institute, Queensland University of Technology, Brisbane, QLD, Australia
| | - Ricardo T. Fujiwara
- Department of Parasitology, Biological Sciences Institute, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Pedro Gazzinelli-Guimaraes
- Department of Parasitology, Biological Sciences Institute, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Lilian Bueno
- Department of Parasitology, Biological Sciences Institute, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Vitor Mati
- Department of Health Sciences, Universidade Federal de Lavras, Lavras, Brazil
| | - Jeffrey M. Bethony
- Department of Microbiology, Immunology and Tropical Medicine, George Washington University, Washington DC, United States of America
| | - Makedonka Mitreva
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Javier Sotillo
- Centre for Molecular Therapeutics, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia
- Centro Nacional de Microbiología, Instituto de Salud Carlos III, Majadahonda, Madrid, Spain
- * E-mail: (JS); (AL)
| | - Alex Loukas
- Centre for Molecular Therapeutics, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia
- * E-mail: (JS); (AL)
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6
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Prasad TSK, Mohanty AK, Kumar M, Sreenivasamurthy SK, Dey G, Nirujogi RS, Pinto SM, Madugundu AK, Patil AH, Advani J, Manda SS, Gupta MK, Dwivedi SB, Kelkar DS, Hall B, Jiang X, Peery A, Rajagopalan P, Yelamanchi SD, Solanki HS, Raja R, Sathe GJ, Chavan S, Verma R, Patel KM, Jain AP, Syed N, Datta KK, Khan AA, Dammalli M, Jayaram S, Radhakrishnan A, Mitchell CJ, Na CH, Kumar N, Sinnis P, Sharakhov IV, Wang C, Gowda H, Tu Z, Kumar A, Pandey A. Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes. Genome Res 2016; 27:133-144. [PMID: 28003436 PMCID: PMC5204337 DOI: 10.1101/gr.201368.115] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Accepted: 11/10/2016] [Indexed: 01/05/2023]
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.
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Affiliation(s)
- T S Keshava Prasad
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,YU-IOB Center for Systems Biology and Molecular Medicine, Yenepoya University, Mangalore 575018, India.,NIMHANS-IOB Proteomics and Bioinformatics Laboratory, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, Karnataka 560029, India
| | - Ajeet Kumar Mohanty
- National Institute of Malaria Research, Field Station, Goa 403001, India.,Department of Zoology, Goa University, Taleigao Plateau, Goa 403206, India
| | - Manish Kumar
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Sreelakshmi K Sreenivasamurthy
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Gourav Dey
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Raja Sekhar Nirujogi
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Centre for Bioinformatics, Pondicherry University, Puducherry 605014, India
| | - Sneha M Pinto
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,YU-IOB Center for Systems Biology and Molecular Medicine, Yenepoya University, Mangalore 575018, India
| | - Anil K Madugundu
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Centre for Bioinformatics, Pondicherry University, Puducherry 605014, India
| | - Arun H Patil
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Jayshree Advani
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Srikanth S Manda
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Centre for Bioinformatics, Pondicherry University, Puducherry 605014, India
| | - Manoj Kumar Gupta
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Sutopa B Dwivedi
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India
| | - Dhanashree S Kelkar
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India
| | - Brantley Hall
- Department of Biochemistry, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA
| | - Xiaofang Jiang
- Department of Biochemistry, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA
| | - Ashley Peery
- Department of Entomology, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA
| | - Pavithra Rajagopalan
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Soujanya D Yelamanchi
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Hitendra S Solanki
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Remya Raja
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India
| | - Gajanan J Sathe
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Sandip Chavan
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Renu Verma
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Krishna M Patel
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India
| | - Ankit P Jain
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Nazia Syed
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Department of Biochemistry and Molecular Biology, Pondicherry University, Puducherry 605014, India
| | - Keshava K Datta
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Aafaque Ahmed Khan
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Manjunath Dammalli
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Department of Biotechnology, Siddaganga Institute of Technology, Tumkur, Karnataka 572103, India
| | - Savita Jayaram
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Aneesha Radhakrishnan
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,Department of Biochemistry and Molecular Biology, Pondicherry University, Puducherry 605014, India
| | - Christopher J Mitchell
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Chan-Hyun Na
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland 21205, USA
| | - Nirbhay Kumar
- Department of Tropical Medicine, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana 70112, USA
| | - Photini Sinnis
- Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA
| | - Igor V Sharakhov
- Department of Entomology, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA
| | - Charles Wang
- Center for Genomics and Department of Basic Sciences, School of Medicine, Loma Linda University, Loma Linda, California 92350, USA
| | - Harsha Gowda
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,YU-IOB Center for Systems Biology and Molecular Medicine, Yenepoya University, Mangalore 575018, India
| | - Zhijian Tu
- Department of Biochemistry, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA
| | - Ashwani Kumar
- National Institute of Malaria Research, Field Station, Goa 403001, India
| | - Akhilesh Pandey
- Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560066, India.,McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.,Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.,Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.,Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
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7
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Li R, Liao G, Nirujogi RS, Pinto SM, Shaw PG, Huang TC, Wan J, Qian J, Gowda H, Wu X, Lv DW, Zhang K, Manda SS, Pandey A, Hayward SD. Phosphoproteomic Profiling Reveals Epstein-Barr Virus Protein Kinase Integration of DNA Damage Response and Mitotic Signaling. PLoS Pathog 2015; 11:e1005346. [PMID: 26714015 PMCID: PMC4699913 DOI: 10.1371/journal.ppat.1005346] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Accepted: 11/28/2015] [Indexed: 12/21/2022] Open
Abstract
Epstein-Barr virus (EBV) is etiologically linked to infectious mononucleosis and several human cancers. EBV encodes a conserved protein kinase BGLF4 that plays a key role in the viral life cycle. To provide new insight into the host proteins regulated by BGLF4, we utilized stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomics to compare site-specific phosphorylation in BGLF4-expressing Akata B cells. Our analysis revealed BGLF4-mediated hyperphosphorylation of 3,046 unique sites corresponding to 1,328 proteins. Frequency analysis of these phosphosites revealed a proline-rich motif signature downstream of BGLF4, indicating a broader substrate recognition for BGLF4 than its cellular ortholog cyclin-dependent kinase 1 (CDK1). Further, motif analysis of the hyperphosphorylated sites revealed enrichment in ATM, ATR and Aurora kinase substrates while functional analyses revealed significant enrichment of pathways related to the DNA damage response (DDR), mitosis and cell cycle. Phosphorylation of proteins associated with the mitotic spindle assembly checkpoint (SAC) indicated checkpoint activation, an event that inactivates the anaphase promoting complex/cyclosome, APC/C. Furthermore, we demonstrated that BGLF4 binds to and directly phosphorylates the key cellular proteins PP1, MPS1 and CDC20 that lie upstream of SAC activation and APC/C inhibition. Consistent with APC/C inactivation, we found that BGLF4 stabilizes the expression of many known APC/C substrates. We also noted hyperphosphorylation of 22 proteins associated the nuclear pore complex, which may contribute to nuclear pore disassembly and SAC activation. A drug that inhibits mitotic checkpoint activation also suppressed the accumulation of extracellular EBV virus. Taken together, our data reveal that, in addition to the DDR, manipulation of mitotic kinase signaling and SAC activation are mechanisms associated with lytic EBV replication. All MS data have been deposited in the ProteomeXchange with identifier PXD002411 (http://proteomecentral.proteomexchange.org/dataset/PXD002411). Epstein-Barr virus (EBV) is a herpesvirus that is associated with B cell and epithelial human cancers. Herpesviruses encode a protein kinase which is an important regulator of lytic virus replication and is consequently a target for anti-viral drug development. The EBV genome encodes for a serine/threonine protein kinase called BGLF4. Previous work on BGLF4 has largely focused on its cyclin-dependent kinase 1 (CDK1)-like activity. The range of BGLF4 cellular substrates and the full impact of BGLF4 on the intracellular microenvironment still remain to be elucidated. Here, we utilized unbiased quantitative phosphoproteomic approach to dissect the changes in the cellular phosphoproteome that are mediated by BGLF4. Our MS analyses revealed extensive hyperphosphorylation of substrates that are normally targeted by CDK1, Ataxia telangiectasia mutated (ATM), Ataxia telangiectasia and Rad3-related (ATR) proteins and Aurora kinases. The up-regulated phosphoproteins were functionally linked to the DNA damage response, mitosis and cell cycle pathways. Our data demonstrate widespread changes in the cellular phosphoproteome that occur upon BGLF4 expression and suggest that manipulation of the DNA damage and mitotic kinase signaling pathways are central to efficient EBV lytic replication.
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Affiliation(s)
- Renfeng Li
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Philips Institute for Oral Health Research, VCU School of Dentistry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- * E-mail: (RL); (AP); (SDH)
| | - Gangling Liao
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Raja Sekhar Nirujogi
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Institute of Bioinformatics, International Technology Park, Bangalore, India
| | - Sneha M. Pinto
- Institute of Bioinformatics, International Technology Park, Bangalore, India
| | - Patrick G. Shaw
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Tai-Chung Huang
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Jun Wan
- Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Jiang Qian
- Massey Cancer Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Harsha Gowda
- Institute of Bioinformatics, International Technology Park, Bangalore, India
| | - Xinyan Wu
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Dong-Wen Lv
- Philips Institute for Oral Health Research, VCU School of Dentistry, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Kun Zhang
- Philips Institute for Oral Health Research, VCU School of Dentistry, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Srikanth S. Manda
- Philips Institute for Oral Health Research, VCU School of Dentistry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Akhilesh Pandey
- Philips Institute for Oral Health Research, VCU School of Dentistry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Diana Helis Henry Medical Research Foundation, New Orleans, Louisiana, United States of America
- * E-mail: (RL); (AP); (SDH)
| | - S. Diane Hayward
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- * E-mail: (RL); (AP); (SDH)
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8
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Mitchell CJ, Getnet D, Kim MS, Manda SS, Kumar P, Huang TC, Pinto SM, Nirujogi RS, Iwasaki M, Shaw PG, Wu X, Zhong J, Chaerkady R, Marimuthu A, Muthusamy B, Sahasrabuddhe NA, Raju R, Bowman C, Danilova L, Cutler J, Kelkar DS, Drake CG, Prasad TSK, Marchionni L, Murakami PN, Scott AF, Shi L, Thierry-Mieg J, Thierry-Mieg D, Irizarry R, Cope L, Ishihama Y, Wang C, Gowda H, Pandey A. A multi-omic analysis of human naïve CD4+ T cells. BMC Syst Biol 2015; 9:75. [PMID: 26542228 PMCID: PMC4636073 DOI: 10.1186/s12918-015-0225-4] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 10/28/2015] [Indexed: 12/21/2022]
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, miRNA-Seq, proteomics, and phosphoproteomics, we derived an integrated and comparative map of these two closely related immune cells and identified potential molecular effectors of immune cell differentiation following antigen encounter. Electronic supplementary material The online version of this article (doi:10.1186/s12918-015-0225-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Christopher J Mitchell
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Derese Getnet
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Min-Sik Kim
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Srikanth S Manda
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | - Praveen Kumar
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | - Tai-Chung Huang
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Sneha M Pinto
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | - Raja Sekhar Nirujogi
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | - Mio Iwasaki
- Department of Molecular & Cellular BioAnalysis, Kyoto University, Kyoto, Japan.
| | - Patrick G Shaw
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Xinyan Wu
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Jun Zhong
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Raghothama Chaerkady
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Arivusudar Marimuthu
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | | | | | - Rajesh Raju
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | - Caitlyn Bowman
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Ludmila Danilova
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Jevon Cutler
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Dhanashree S Kelkar
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | - Charles G Drake
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - T S Keshava Prasad
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | - Luigi Marchionni
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Peter N Murakami
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
| | - Alan F Scott
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Leming Shi
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, USA.
| | - Jean Thierry-Mieg
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA.
| | - Danielle Thierry-Mieg
- National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA.
| | - Rafael Irizarry
- Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, MA, USA.
| | - Leslie Cope
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Yasushi Ishihama
- Department of Molecular & Cellular BioAnalysis, Kyoto University, Kyoto, Japan.
| | - Charles Wang
- Center for Genomics and Division of Microbiology & Molecular Genetics, Loma Linda University, Loma Linda, CA, USA.
| | - Harsha Gowda
- Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India.
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Institute of Bioinformatics, International Tech Park, Whitefield, Bangalore, India. .,Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Department of Pathology and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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9
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Beachley VZ, Wolf MT, Sadtler K, Manda SS, Jacobs H, Blatchley MR, Bader JS, Pandey A, Pardoll D, Elisseeff JH. Tissue matrix arrays for high-throughput screening and systems analysis of cell function. Nat Methods 2015; 12:1197-204. [PMID: 26480475 PMCID: PMC4666781 DOI: 10.1038/nmeth.3619] [Citation(s) in RCA: 120] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2015] [Accepted: 09/02/2015] [Indexed: 02/07/2023]
Abstract
Cell and protein arrays have demonstrated remarkable utility in the high-throughput evaluation of biological responses; however, they lack the complexity of native tissue and organs. Here, we describe tissue extracellular matrix (ECM) arrays for screening biological outputs and systems analysis. We spotted processed tissue ECM particles as two-dimensional arrays or incorporated them with cells to generate three-dimensional cell-matrix microtissue arrays. We then investigated the response of human stem, cancer, and immune cells to tissue ECM arrays originating from 11 different tissues, and validated the 2D and 3D arrays as representative of the in vivo microenvironment through quantitative analysis of tissue-specific cellular responses, including matrix production, adhesion and proliferation, and morphological changes following culture. The biological outputs correlated with tissue proteomics, and network analysis identified several proteins linked to cell function. Our methodology enables broad screening of ECMs to connect tissue-specific composition with biological activity, providing a new resource for biomaterials research and translation.
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Affiliation(s)
- Vince Z Beachley
- Translational Tissue Engineering Center, Wilmer Eye Institute and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Rowan University, Glassboro, New Jersey, USA
| | - Matthew T Wolf
- Translational Tissue Engineering Center, Wilmer Eye Institute and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Kaitlyn Sadtler
- Translational Tissue Engineering Center, Wilmer Eye Institute and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Srikanth S Manda
- McKusick-Nathans Institute of Genetic Medicine, Baltimore, Maryland, USA.,Institute of Bioinformatics, International Technology Park, Bangalore, India
| | - Heather Jacobs
- Translational Tissue Engineering Center, Wilmer Eye Institute and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Michael R Blatchley
- Translational Tissue Engineering Center, Wilmer Eye Institute and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Joel S Bader
- High-Throughput Biology Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine, Baltimore, Maryland, USA.,Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Drew Pardoll
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jennifer H Elisseeff
- Translational Tissue Engineering Center, Wilmer Eye Institute and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
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10
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Nirujogi RS, Wright JD, Manda SS, Zhong J, Na CH, Meyerhoff J, Benton B, Jabbour R, Willis K, Kim MS, Pandey A, Sekowski JW. Phosphoproteomic analysis reveals compensatory effects in the piriform cortex of VX nerve agent exposed rats. Proteomics 2015; 15:487-99. [PMID: 25403869 DOI: 10.1002/pmic.201400371] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2014] [Revised: 10/01/2014] [Accepted: 11/12/2014] [Indexed: 01/15/2023]
Abstract
To gain insights into the toxicity induced by the nerve agent VX, an MS-based phosphoproteomic analysis was carried out on the piriform cortex region of brains from VX-treated rats. Using isobaric tag based TMT labeling followed by titanium dioxide enrichment strategy, we identified 9975 unique phosphosites derived from 3287 phosphoproteins. Temporal changes in the phosphorylation status of peptides were observed over a time period of 24 h in rats exposed to a 1× LD50, intravenous (i.v.) dose with the most notable changes occurring at the 1 h postexposure time point. Five major functional classes of proteins exhibited changes in their phosphorylation status: (i) ion channels/transporters, including ATPases, (ii) kinases/phosphatases, (iii) GTPases, (iv) structural proteins, and (v) transcriptional regulatory proteins. This study is the first quantitative phosphoproteomic analysis of VX toxicity in the brain. Understanding the toxicity and compensatory signaling mechanisms will improve the understanding of the complex toxicity of VX in the brain and aid in the elucidation of novel molecular targets that would be important for development of improved countermeasures. All MS data have been deposited in the ProteomeXchange with identifier PXD001184 (http://proteomecentral.proteomexchange.org/dataset/PXD001184).
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Affiliation(s)
- Raja Sekhar Nirujogi
- Institute of Bioinformatics, International Tech Park, Bangalore, India; School of Life Sciences, Centre for Bioinformatics, Pondicherry University, Puducherry, India; Department of Neuroscience, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
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11
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Pinto SM, Nirujogi RS, Rojas PL, Patil AH, Manda SS, Subbannayya Y, Roa JC, Chatterjee A, Prasad TSK, Pandey A. Quantitative phosphoproteomic analysis of IL-33-mediated signaling. Proteomics 2015; 15:532-44. [PMID: 25367039 DOI: 10.1002/pmic.201400303] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2014] [Revised: 09/25/2014] [Accepted: 10/28/2014] [Indexed: 12/13/2022]
Abstract
Interleukin-33 (IL-33) is a novel member of the IL-1 family of cytokines that plays diverse roles in the regulation of immune responses. IL-33 exerts its effects through a heterodimeric receptor complex resulting in the production and release of proinflammatory cytokines. A detailed understanding of the signaling pathways activated by IL-33 is still unclear. To gain insights into the IL-33-mediated signaling mechanisms, we carried out a SILAC-based global quantitative phosphoproteomic analysis that resulted in the identification of 7191 phosphorylation sites derived from 2746 proteins. We observed alterations in the level of phosphorylation in 1050 sites corresponding to 672 proteins upon IL-33 stimulation. We report, for the first time, phosphorylation of multiple protein kinases, including mitogen-activated protein kinase activated protein kinase 2 (Mapkapk2), receptor (TNFRSF) interacting serine-threonine kinase 1 (Ripk1), and NAD kinase (Nadk) that are induced by IL-33. In addition, we observed IL-33-induced phosphorylation of several protein phosphatases including protein tyrosine phosphatase, nonreceptor-type 12 (Ptpn12), and inositol polyphosphate-5-phosphatase D (Inpp5d), which have not been reported previously. Network analysis revealed an enrichment of actin binding and cytoskeleton reorganization that could be important in macrophage activation induced by IL-33. Our study is the first quantitative analysis of IL-33-regulated phosphoproteome. Our findings significantly expand the understanding of IL-33-mediated signaling events and have the potential to provide novel therapeutic targets pertaining to immune-related diseases such as asthma where dysregulation of IL-33 is observed. All MS data have been deposited in the ProteomeXchange with identifier PXD000984 (http://proteomecentral.proteomexchange.org/dataset/PXD000984).
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Affiliation(s)
- Sneha M Pinto
- Institute of Bioinformatics, International Technology Park, Bangalore, India; Manipal University, Madhava Nagar, Manipal, India; McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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12
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Wu X, Zahari MS, Renuse S, Nirujogi RS, Kim MS, Manda SS, Stearns V, Gabrielson E, Sukumar S, Pandey A. Phosphoproteomic Analysis Identifies Focal Adhesion Kinase 2 (FAK2) as a Potential Therapeutic Target for Tamoxifen Resistance in Breast Cancer. Mol Cell Proteomics 2015; 14:2887-900. [PMID: 26330541 DOI: 10.1074/mcp.m115.050484] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Indexed: 01/13/2023] Open
Abstract
Tamoxifen, an estrogen receptor-α (ER) antagonist, is an important agent for the treatment of breast cancer. However, this therapy is complicated by the fact that a substantial number of patients exhibit either de novo or acquired resistance. To characterize the signaling mechanisms underlying this resistance, we treated the MCF7 breast cancer cell line with tamoxifen for over six months and showed that this cell line acquired resistance to tamoxifen in vitro and in vivo. We performed SILAC-based quantitative phosphoproteomic profiling on the tamoxifen resistant and vehicle-treated sensitive cell lines to quantify the phosphorylation alterations associated with tamoxifen resistance. From >5600 unique phosphopeptides identified, 1529 peptides exhibited hyperphosphorylation and 409 peptides showed hypophosphorylation in the tamoxifen resistant cells. Gene set enrichment analysis revealed that focal adhesion pathway was one of the most enriched signaling pathways activated in tamoxifen resistant cells. Significantly, we showed that the focal adhesion kinase FAK2 was not only hyperphosphorylated but also transcriptionally up-regulated in tamoxifen resistant cells. FAK2 suppression by specific siRNA knockdown or a small molecule inhibitor repressed cellular proliferation in vitro and tumor formation in vivo. More importantly, our survival analysis revealed that high expression of FAK2 is significantly associated with shorter metastasis-free survival in estrogen receptor-positive breast cancer patients treated with tamoxifen. Our studies suggest that FAK2 is a potential therapeutic target for the management of hormone-refractory breast cancers.
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Affiliation(s)
- Xinyan Wu
- From the ‡McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
| | - Muhammad Saddiq Zahari
- From the ‡McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
| | - Santosh Renuse
- §Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
| | - Raja Sekhar Nirujogi
- §Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
| | - Min-Sik Kim
- From the ‡McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
| | - Srikanth S Manda
- §Institute of Bioinformatics, International Technology Park, Bangalore, 560066 India
| | | | - Edward Gabrielson
- ‖Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231
| | | | - Akhilesh Pandey
- From the ‡McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205; ¶Department of Oncology; ‖Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231
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13
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Ewing AD, Gacita A, Wood LD, Ma F, Xing D, Kim MS, Manda SS, Abril G, Pereira G, Makohon-Moore A, Looijenga LHJ, Gillis AJM, Hruban RH, Anders RA, Romans KE, Pandey A, Iacobuzio-Donahue CA, Vogelstein B, Kinzler KW, Kazazian HH, Solyom S. Widespread somatic L1 retrotransposition occurs early during gastrointestinal cancer evolution. Genome Res 2015; 25:1536-45. [PMID: 26260970 PMCID: PMC4579339 DOI: 10.1101/gr.196238.115] [Citation(s) in RCA: 93] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2015] [Accepted: 08/10/2015] [Indexed: 01/27/2023]
Abstract
Somatic L1 retrotransposition events have been shown to occur in epithelial cancers. Here, we attempted to determine how early somatic L1 insertions occurred during the development of gastrointestinal (GI) cancers. Using L1-targeted resequencing (L1-seq), we studied different stages of four colorectal cancers arising from colonic polyps, seven pancreatic carcinomas, as well as seven gastric cancers. Surprisingly, we found somatic L1 insertions not only in all cancer types and metastases but also in colonic adenomas, well-known cancer precursors. Some insertions were also present in low quantities in normal GI tissues, occasionally caught in the act of being clonally fixed in the adjacent tumors. Insertions in adenomas and cancers numbered in the hundreds, and many were present in multiple tumor sections, implying clonal distribution. Our results demonstrate that extensive somatic insertional mutagenesis occurs very early during the development of GI tumors, probably before dysplastic growth.
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Affiliation(s)
- Adam D Ewing
- Mater Research Institute, University of Queensland, Woolloongabba, Queensland 4102, Australia
| | - Anthony Gacita
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Laura D Wood
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins Medical Institutions, Baltimore, Maryland 21231, USA
| | - Florence Ma
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Dongmei Xing
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins Medical Institutions, Baltimore, Maryland 21231, USA
| | - Min-Sik Kim
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Srikanth S Manda
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Gabriela Abril
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Gavin Pereira
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Alvin Makohon-Moore
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins Medical Institutions, Baltimore, Maryland 21231, USA
| | - Leendert H J Looijenga
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
| | - Ad J M Gillis
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
| | - Ralph H Hruban
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins Medical Institutions, Baltimore, Maryland 21231, USA
| | - Robert A Anders
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins Medical Institutions, Baltimore, Maryland 21231, USA
| | - Katharine E Romans
- The Johns Hopkins University School of Medicine Cancer Biology, Baltimore, Maryland 21205, USA
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Christine A Iacobuzio-Donahue
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins Medical Institutions, Baltimore, Maryland 21231, USA
| | - Bert Vogelstein
- The Ludwig Center and The Howard Hughes Medical Institute at Johns Hopkins Kimmel Cancer Center, Baltimore, Maryland 21287, USA
| | - Kenneth W Kinzler
- The Ludwig Center and The Howard Hughes Medical Institute at Johns Hopkins Kimmel Cancer Center, Baltimore, Maryland 21287, USA
| | - Haig H Kazazian
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Szilvia Solyom
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
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14
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Subbannayya Y, Mir SA, Renuse S, Manda SS, Pinto SM, Puttamallesh VN, Solanki HS, Manju HC, Syed N, Sharma R, Christopher R, Vijayakumar M, Veerendra Kumar KV, Keshava Prasad TS, Ramaswamy G, Kumar RV, Chatterjee A, Pandey A, Gowda H. Identification of differentially expressed serum proteins in gastric adenocarcinoma. J Proteomics 2015; 127:80-8. [PMID: 25952687 DOI: 10.1016/j.jprot.2015.04.021] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Revised: 04/14/2015] [Accepted: 04/21/2015] [Indexed: 01/01/2023]
Abstract
UNLABELLED Gastric adenocarcinoma is an aggressive cancer with poor prognosis. Blood based biomarkers of gastric cancer have the potential to improve diagnosis and monitoring of these tumors. Proteins that show altered levels in the circulation of gastric cancer patients could prove useful as putative biomarkers. We used an iTRAQ-based quantitative proteomic approach to identify proteins that show altered levels in the sera of patients with gastric cancer. Our study resulted in identification of 643 proteins, of which 48 proteins showed increased levels and 11 proteins showed decreased levels in serum from gastric cancer patients compared to age and sex matched healthy controls. Proteins that showed increased expression in gastric cancer included inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), Mannose-binding protein C (MBL2), sex hormone-binding globulin (SHBG), insulin-like growth factor-binding protein 2 (IGFBP2), serum amyloid A protein (SAA1), Orosomucoid 1 (ORM1) and extracellular superoxide dismutase [Cu-Zn] (SOD3). We used multiple reaction monitoring assays and validated elevated levels of ITIH4 and SAA1 proteins in serum from gastric cancer patients. BIOLOGICAL SIGNIFICANCE Gastric cancer is a highly aggressive cancer associated with high mortality. Serum-based biomarkers are of considerable interest in diagnosis and monitoring of various diseases including cancers. Gastric cancer is often diagnosed at advanced stages resulting in poor prognosis and high mortality. Pathological diagnosis using biopsy specimens remains the gold standard for diagnosis of gastric cancer. Serum-based biomarkers are of considerable importance as they are minimally invasive. In this study, we carried out quantitative proteomic profiling of serum from gastric cancer patients to identify proteins that show altered levels in gastric cancer patients. We identified more than 50 proteins that showed altered levels in gastric cancer patient sera. Validation in a large cohort of well classified patient samples would prove useful in identifying novel blood based biomarkers for gastric cancers. This article is part of a Special Issue entitled: Proteomics in India.
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Affiliation(s)
- Yashwanth Subbannayya
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India; Rajiv Gandhi University of Health Sciences, Bangalore 560041, Karnataka, India; Department of Biochemistry, Kidwai Memorial Institute of Oncology, Bangalore 560029, Karnataka, India
| | - Sartaj Ahmad Mir
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India; Manipal University, Manipal 576 104, Karnataka, India
| | - Santosh Renuse
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India; School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam 690525, India
| | - Srikanth S Manda
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India; Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605014, India
| | - Sneha M Pinto
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India; Manipal University, Manipal 576 104, Karnataka, India
| | | | | | - H C Manju
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India
| | - Nazia Syed
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India; Department of Biochemistry and Molecular Biology, School of Life Sciences, Pondicherry University, Puducherry 605014, India
| | - Rakesh Sharma
- Department of Neurochemistry, National Institute of Mental Health and Neurosciences, Bangalore 560029, Karnataka, India
| | - Rita Christopher
- Department of Neurochemistry, National Institute of Mental Health and Neurosciences, Bangalore 560029, Karnataka, India
| | - M Vijayakumar
- Department of Surgery, Kidwai Memorial Institute of Oncology, Bangalore 560029, Karnataka, India
| | - K V Veerendra Kumar
- Department of Surgery, Kidwai Memorial Institute of Oncology, Bangalore 560029, Karnataka, India
| | - T S Keshava Prasad
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India
| | - Girija Ramaswamy
- Department of Biochemistry, Kidwai Memorial Institute of Oncology, Bangalore 560029, Karnataka, India
| | - Rekha V Kumar
- Department of Pathology, Kidwai Memorial Institute of Oncology, Bangalore 560029, Karnataka, India
| | - Aditi Chatterjee
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Harsha Gowda
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India.
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15
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Murthy KR, Rajagopalan P, Pinto SM, Advani J, Murthy PR, Goel R, Subbannayya Y, Balakrishnan L, Dash M, Anil AK, Manda SS, Nirujogi RS, Kelkar DS, Sathe GJ, Dey G, Chatterjee A, Gowda H, Chakravarti S, Shankar S, Sahasrabuddhe NA, Nair B, Somani BL, Prasad TSK, Pandey A. Proteomics of Human Aqueous Humor. OMICS: A Journal of Integrative Biology 2015; 19:283-93. [DOI: 10.1089/omi.2015.0029] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Krishna R. Murthy
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Department of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam, India
- Vittala International Institute of Ophthalmology, Bangalore, India
| | - Pavithra Rajagopalan
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- School of Biotechnology, KIIT University, Bhubaneswar, India
| | - Sneha M. Pinto
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Manipal University, Madhav Nagar, Manipal, Karnataka, India
| | - Jayshree Advani
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Manipal University, Madhav Nagar, Manipal, Karnataka, India
| | | | - Renu Goel
- Institute of Bioinformatics, International Tech Park, Bangalore, India
| | - Yashwanth Subbannayya
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Rajiv Gandhi University of Health Sciences, Bangalore, India
| | - Lavanya Balakrishnan
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Department of Biotechnology, Kuvempu University, Shankaraghatta, India
| | - Mahashweta Dash
- Department of Internal Medicine, Armed Forces Medical College, Pune, India
| | - Abhijith K. Anil
- Department of Internal Medicine, Armed Forces Medical College, Pune, India
| | - Srikanth S. Manda
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, India
| | - Raja Sekhar Nirujogi
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, India
| | | | - Gajanan J. Sathe
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Manipal University, Madhav Nagar, Manipal, Karnataka, India
| | - Gourav Dey
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Manipal University, Madhav Nagar, Manipal, Karnataka, India
| | - Aditi Chatterjee
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- School of Biotechnology, KIIT University, Bhubaneswar, India
| | - Harsha Gowda
- Institute of Bioinformatics, International Tech Park, Bangalore, India
| | - Shukti Chakravarti
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Subramanian Shankar
- Department of Rheumatology, Medical Division, Command Hospital (Air Force), Bangalore, India
| | | | - Bipin Nair
- Department of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam, India
| | - Babu Lal Somani
- Institute of Bioinformatics, International Tech Park, Bangalore, India
| | - T. S. Keshava Prasad
- Institute of Bioinformatics, International Tech Park, Bangalore, India
- Department of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam, India
- Manipal University, Madhav Nagar, Manipal, Karnataka, India
- Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry, India
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
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16
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Kelkar DS, Provost E, Chaerkady R, Muthusamy B, Manda SS, Subbannayya T, Selvan LDN, Wang CH, Datta KK, Woo S, Dwivedi SB, Renuse S, Getnet D, Huang TC, Kim MS, Pinto SM, Mitchell CJ, Madugundu AK, Kumar P, Sharma J, Advani J, Dey G, Balakrishnan L, Syed N, Nanjappa V, Subbannayya Y, Goel R, Prasad TSK, Bafna V, Sirdeshmukh R, Gowda H, Wang C, Leach SD, Pandey A. Annotation of the zebrafish genome through an integrated transcriptomic and proteomic analysis. Mol Cell Proteomics 2014; 13:3184-98. [PMID: 25060758 DOI: 10.1074/mcp.m114.038299] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Accurate annotation of protein-coding genes is one of the primary tasks upon the completion of whole genome sequencing of any organism. In this study, we used an integrated transcriptomic and proteomic strategy to validate and improve the existing zebrafish genome annotation. We undertook high-resolution mass-spectrometry-based proteomic profiling of 10 adult organs, whole adult fish body, and two developmental stages of zebrafish (SAT line), in addition to transcriptomic profiling of six organs. More than 7,000 proteins were identified from proteomic analyses, and ∼ 69,000 high-confidence transcripts were assembled from the RNA sequencing data. Approximately 15% of the transcripts mapped to intergenic regions, the majority of which are likely long non-coding RNAs. These high-quality transcriptomic and proteomic data were used to manually reannotate the zebrafish genome. We report the identification of 157 novel protein-coding genes. In addition, our data led to modification of existing gene structures including novel exons, changes in exon coordinates, changes in frame of translation, translation in annotated UTRs, and joining of genes. Finally, we discovered four instances of genome assembly errors that were supported by both proteomic and transcriptomic data. Our study shows how an integrative analysis of the transcriptome and the proteome can extend our understanding of even well-annotated genomes.
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Affiliation(s)
- Dhanashree S Kelkar
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‡Amrita School of Biotechnology, Amrita University, Kollam 690 525, India
| | - Elayne Provost
- §Department of Surgery, Johns Hopkins University, Baltimore, Maryland 21205
| | - Raghothama Chaerkady
- ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205
| | - Babylakshmi Muthusamy
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‖Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605014, India
| | - Srikanth S Manda
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‖Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605014, India; **Departments of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
| | - Tejaswini Subbannayya
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‡Amrita School of Biotechnology, Amrita University, Kollam 690 525, India
| | - Lakshmi Dhevi N Selvan
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‡Amrita School of Biotechnology, Amrita University, Kollam 690 525, India
| | - Chieh-Huei Wang
- ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205
| | - Keshava K Datta
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‡‡School of Biotechnology, KIIT University, Bhubaneswar, Odisha 751024, India
| | - Sunghee Woo
- §§Department of Computer Science, University of California, San Diego, California 92093
| | - Sutopa B Dwivedi
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‡Amrita School of Biotechnology, Amrita University, Kollam 690 525, India
| | - Santosh Renuse
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‡Amrita School of Biotechnology, Amrita University, Kollam 690 525, India
| | - Derese Getnet
- ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205
| | - Tai-Chung Huang
- ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205
| | - Min-Sik Kim
- ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205; **Departments of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
| | - Sneha M Pinto
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205; ¶¶Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Christopher J Mitchell
- ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205
| | - Anil K Madugundu
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India
| | - Praveen Kumar
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India
| | - Jyoti Sharma
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ¶¶Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Jayshree Advani
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India
| | - Gourav Dey
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ¶¶Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Lavanya Balakrishnan
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‖‖Department of Biotechnology, Kuvempu University, Shimoga 577 451, India
| | - Nazia Syed
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; Department of Biochemistry and Molecular Biology, School of Life Sciences, Pondicherry University, Puducherry 605 014, India
| | - Vishalakshi Nanjappa
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‡Amrita School of Biotechnology, Amrita University, Kollam 690 525, India
| | - Yashwanth Subbannayya
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India
| | - Renu Goel
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India
| | - T S Keshava Prasad
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ‡Amrita School of Biotechnology, Amrita University, Kollam 690 525, India; ‖Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605014, India; ¶¶Manipal University, Madhav Nagar, Manipal, Karnataka 576104, India
| | - Vineet Bafna
- §§Department of Computer Science, University of California, San Diego, California 92093
| | - Ravi Sirdeshmukh
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India
| | - Harsha Gowda
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India
| | - Charles Wang
- The Center for Genomics and Division of Microbiology & Molecular Genetics, School of Medicine, Loma Linda University, Loma Linda, California 92350;
| | - Steven D Leach
- §Department of Surgery, Johns Hopkins University, Baltimore, Maryland 21205; ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205;
| | - Akhilesh Pandey
- From the *Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India; ¶McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205; **Departments of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205; Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
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17
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Pinto SM, Manda SS, Kim MS, Taylor K, Selvan LDN, Balakrishnan L, Subbannayya T, Yan F, Prasad TSK, Gowda H, Lee C, Hancock WS, Pandey A. Functional annotation of proteome encoded by human chromosome 22. J Proteome Res 2014; 13:2749-60. [PMID: 24669763 PMCID: PMC4059257 DOI: 10.1021/pr401169d] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
![]()
As
part of the chromosome-centric human proteome project (C-HPP)
initiative, we report our progress on the annotation of chromosome 22.
Chromosome 22, spanning 51 million base pairs, was the first chromosome
to be sequenced. Gene dosage alterations on this chromosome have been
shown to be associated with a number of congenital anomalies. In addition,
several rare but aggressive tumors have been associated with this
chromosome. A number of important gene families including immunoglobulin
lambda locus, Crystallin beta family, and APOBEC gene family are located
on this chromosome. On the basis of proteomic profiling of 30 histologically
normal tissues and cells using high-resolution mass spectrometry,
we show protein evidence of 367 genes on chromosome 22. Importantly,
this includes 47 proteins, which are currently annotated as “missing”
proteins. We also confirmed the translation start sites of 120 chromosome 22-encoded
proteins. Employing a comprehensive proteogenomics analysis pipeline,
we provide evidence of novel coding regions on this chromosome which
include upstream ORFs and novel exons in addition to correcting existing
gene structures. We describe tissue-wise expression of the proteins
and the distribution of gene families on this chromosome. These data
have been deposited to ProteomeXchange with the identifier PXD000561.
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Affiliation(s)
- Sneha M Pinto
- Institute of Bioinformatics, International Tech Park , Bangalore, Karnataka 560066, India
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18
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Balakrishnan L, Nirujogi RS, Ahmad S, Bhattacharjee M, Manda SS, Renuse S, Kelkar DS, Subbannayya Y, Raju R, Goel R, Thomas JK, Kaur N, Dhillon M, Tankala SG, Jois R, Vasdev V, Ramachandra Y, Sahasrabuddhe NA, Prasad TK, Mohan S, Gowda H, Shankar S, Pandey A. Proteomic analysis of human osteoarthritis synovial fluid. Clin Proteomics 2014; 11:6. [PMID: 24533825 PMCID: PMC3942106 DOI: 10.1186/1559-0275-11-6] [Citation(s) in RCA: 98] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2013] [Accepted: 01/06/2014] [Indexed: 12/30/2022] Open
Abstract
Background Osteoarthritis 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. Results We 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. Conclusions We 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.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Subramanian Shankar
- Department of Internal Medicine, Armed Forces Medical College, Pune, Maharashtra 411040, India.
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