1501
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Gorini G, Roberts AJ, Mayfield RD. Neurobiological signatures of alcohol dependence revealed by protein profiling. PLoS One 2013; 8:e82656. [PMID: 24358215 PMCID: PMC3865151 DOI: 10.1371/journal.pone.0082656] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2013] [Accepted: 10/24/2013] [Indexed: 01/09/2023] Open
Abstract
Alcohol abuse causes dramatic neuroadaptations in the brain, which contribute to tolerance, dependence, and behavioral modifications. Previous proteomic studies in human alcoholics and animal models have identified candidate alcoholism-related proteins. However, recent evidences suggest that alcohol dependence is caused by changes in co-regulation that are invisible to single protein-based analysis. Here, we analyze global proteomics data to integrate differential expression, co-expression networks, and gene annotations to unveil key neurobiological rearrangements associated with the transition to alcohol dependence modeled by a Chronic Intermittent Ethanol (CIE), two-bottle choice (2BC) paradigm. We analyzed cerebral cortices (CTX) and midbrains (MB) from male C57BL/6J mice subjected to a CIE, 2BC paradigm, which induces heavy drinking and represents one of the best available animal models for alcohol dependence and relapse drinking. CIE induced significant changes in protein levels in dependent mice compared with their non-dependent controls. Multiple protein isoforms showed region-specific differential regulation as a result of post-translational modifications. Our integrative analysis identified modules of co-expressed proteins that were highly correlated with CIE treatment. We found that modules most related to the effects of CIE treatment coordinate molecular imbalances in endocytic- and energy-related pathways, with specific proteins involved, such as dynamin-1. The qRT-PCR experiments validated both differential and co-expression analyses, and the correspondence among our data and previous genomic and proteomic studies in humans and rodents substantiates our findings. The changes identified above may play a key role in the escalation of ethanol consumption associated with dependence. Our approach to alcohol addiction will advance knowledge of brain remodeling mechanisms and adaptive changes in response to drug abuse, contribute to understanding of organizational principles of CTX and MB proteomes, and define potential new molecular targets for treating alcohol addiction. The integrative analysis employed here highlight the advantages of systems approaches in studying the neurobiology of alcohol addiction.
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Affiliation(s)
- Giorgio Gorini
- Waggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, Texas, United States of America
- * E-mail:
| | - Amanda J. Roberts
- Molecular & Cellular Neuroscience Department, The Scripps Research Institute, La Jolla, California, United States of America
| | - R. Dayne Mayfield
- Waggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, Texas, United States of America
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1502
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Carroll AW, Joshi HJ, Heazlewood JL. Managing the green proteomes for the next decade of plant research. FRONTIERS IN PLANT SCIENCE 2013; 4:501. [PMID: 24379820 PMCID: PMC3864100 DOI: 10.3389/fpls.2013.00501] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2013] [Accepted: 11/22/2013] [Indexed: 05/25/2023]
Affiliation(s)
- Andrew W. Carroll
- Department of Cellular and Molecular Medicine, Copenhagen Center for Glycomics, University of CopenhagenCopenhagen, Denmark
| | - Hiren J. Joshi
- Physical Biosciences Division and Joint BioEnergy Institute, Lawrence Berkeley National LaboratoryBerkeley, CA, USA
| | - Joshua L. Heazlewood
- Department of Cellular and Molecular Medicine, Copenhagen Center for Glycomics, University of CopenhagenCopenhagen, Denmark
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1503
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Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics. Nat Methods 2013; 11:167-70. [DOI: 10.1038/nmeth.2767] [Citation(s) in RCA: 324] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2013] [Accepted: 11/05/2013] [Indexed: 12/30/2022]
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1504
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Nynca J, Arnold GJ, Fröhlich T, Otte K, Flenkenthaler F, Ciereszko A. Proteomic identification of rainbow trout seminal plasma proteins. Proteomics 2013; 14:133-40. [DOI: 10.1002/pmic.201300267] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Revised: 10/04/2013] [Accepted: 10/23/2013] [Indexed: 12/23/2022]
Affiliation(s)
- Joanna Nynca
- Department of Gametes and Embryo Biology; Institute of Animal Reproduction and Food Research; Polish Academy of Sciences; Olsztyn Poland
| | - Georg J. Arnold
- Laboratory for Functional Genome Analysis (LAFUGA); Gene Center and Department of Biochemistry; Ludwig-Maximilians-Universität; Munich Germany
- Gene Center and Department of Biochemistry; Ludwig-Maximilians-Universität; Munich Germany
| | - Thomas Fröhlich
- Laboratory for Functional Genome Analysis (LAFUGA); Gene Center and Department of Biochemistry; Ludwig-Maximilians-Universität; Munich Germany
- Gene Center and Department of Biochemistry; Ludwig-Maximilians-Universität; Munich Germany
| | - Kathrin Otte
- Laboratory for Functional Genome Analysis (LAFUGA); Gene Center and Department of Biochemistry; Ludwig-Maximilians-Universität; Munich Germany
- Gene Center and Department of Biochemistry; Ludwig-Maximilians-Universität; Munich Germany
| | - Florian Flenkenthaler
- Laboratory for Functional Genome Analysis (LAFUGA); Gene Center and Department of Biochemistry; Ludwig-Maximilians-Universität; Munich Germany
- Gene Center and Department of Biochemistry; Ludwig-Maximilians-Universität; Munich Germany
| | - Andrzej Ciereszko
- Department of Gametes and Embryo Biology; Institute of Animal Reproduction and Food Research; Polish Academy of Sciences; Olsztyn Poland
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1505
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Krey JF, Wilmarth PA, Shin JB, Klimek J, Sherman NE, Jeffery ED, Choi D, David LL, Barr-Gillespie PG. Accurate label-free protein quantitation with high- and low-resolution mass spectrometers. J Proteome Res 2013; 13:1034-1044. [PMID: 24295401 DOI: 10.1021/pr401017h] [Citation(s) in RCA: 109] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Label-free quantitation of proteins analyzed by tandem mass spectrometry uses either integrated peak intensity from the parent-ion mass analysis (MS1) or features from fragment-ion analysis (MS2), such as spectral counts or summed fragment-ion intensity. We directly compared MS1 and MS2 quantitation by analyzing human protein standards diluted into Escherichia coli extracts on an Orbitrap mass spectrometer. We found that summed MS2 intensities were nearly as accurate as integrated MS1 intensities, and both outperformed MS2 spectral counting in accuracy and linearity. We compared these results to those obtained from two low-resolution ion-trap mass spectrometers; summed MS2 intensities from LTQ and LTQ Velos instruments were similar in accuracy to those from the Orbitrap. Data from all three instruments are available via ProteomeXchange with identifier PXD000602. Abundance measurements using MS1 or MS2 intensities had limitations, however. While measured protein concentration was on average well-correlated with the known concentration, there was considerable protein-to-protein variation. Moreover, not all human proteins diluted to a mole fraction of 10(-3) or lower were detected, with a strong falloff below 10(-4) mole fraction. These results show that MS1 and MS2 intensities are simple measures of protein abundance that are on average accurate but should be limited to quantitation of proteins of intermediate to higher fractional abundance.
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Affiliation(s)
- Jocelyn F Krey
- Oregon Hearing Research Center & Vollum Institute, Oregon Health & Science University, Portland, OR
| | - Phillip A Wilmarth
- Department of Biochemistry and Molecular Biology, Oregon Health & Science University, Portland, OR
| | - Jung-Bum Shin
- Oregon Hearing Research Center & Vollum Institute, Oregon Health & Science University, Portland, OR
| | - John Klimek
- Proteomics Shared Resource, Oregon Health & Science University, Portland, OR
| | - Nicholas E Sherman
- W.M. Keck Biomedical Mass Spectrometry Lab, University of Virginia, Charlottesville, VA
| | - Erin D Jeffery
- W.M. Keck Biomedical Mass Spectrometry Lab, University of Virginia, Charlottesville, VA
| | - Dongseok Choi
- Department of Public Health & Preventative Medicine, Oregon Health & Science University, Portland, OR
| | - Larry L David
- Department of Biochemistry and Molecular Biology, Oregon Health & Science University, Portland, OR.,Proteomics Shared Resource, Oregon Health & Science University, Portland, OR
| | - Peter G Barr-Gillespie
- Oregon Hearing Research Center & Vollum Institute, Oregon Health & Science University, Portland, OR
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1506
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Genotoxic stress prevents Ndd1-dependent transcriptional activation of G2/M-specific genes in Saccharomyces cerevisiae. Mol Cell Biol 2013; 34:711-24. [PMID: 24324010 DOI: 10.1128/mcb.01090-13] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Downregulation of specific transcripts is one of the mechanisms utilized by eukaryotic checkpoint systems to prevent cell cycle progression. Here we identified and explored such a mechanism in the yeast Saccharomyces cerevisiae. It involves the Mec1-Rad53 kinase cascade, which attenuates G(2)/M-specific gene transcription upon genotoxic stress. This inhibition is achieved via multiple Rad53-dependent inhibitory phosphorylations on the transcriptional activator Ndd1 that prevent its chromatin recruitment via interactions with the forkhead factor Fkh2. Relevant modification sites on Ndd1 were identified by mass spectrometry, and corresponding alanine substitutions were able to suppress a methyl methanesulfonate-induced block in Ndd1 chromatin recruitment. Whereas effective suppression by these Ndd1 mutants is achieved for DNA damage, this is not the case under replication stress conditions, suggesting that additional mechanisms must operate under such conditions. We propose that budding yeast cells prevent the normal transcription of G(2)/M-specific genes upon genotoxic stress to precisely coordinate the timing of mitotic and postmitotic events with respect to S phase.
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1507
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Boonla C, Tosukhowong P, Spittau B, Schlosser A, Pimratana C, Krieglstein K. Inflammatory and fibrotic proteins proteomically identified as key protein constituents in urine and stone matrix of patients with kidney calculi. Clin Chim Acta 2013; 429:81-9. [PMID: 24333391 DOI: 10.1016/j.cca.2013.11.036] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Revised: 11/27/2013] [Accepted: 11/27/2013] [Indexed: 11/19/2022]
Abstract
To uncover whether urinary proteins are incorporated into stones, the proteomic profiles of kidney stones and urine collected from the same patients have to be explored. We employed 1D-PAGE and nanoHPLC-ESI-MS/MS to analyze the proteomes of kidney stone matrix (n=16), nephrolithiatic urine (n=14) and healthy urine (n=3). We identified 62, 66 and 22 proteins in stone matrix, nephrolithiatic urine and healthy urine, respectively. Inflammation- and fibrosis-associated proteins were frequently detected in the stone matrix and nephrolithiatic urine. Eighteen proteins were exclusively found in the stone matrix and nephrolithiatic urine, considered as candidate biomarkers for kidney stone formation. S100A8 and fibronectin, representatives of inflammation and fibrosis, respectively, were up-regulated in nephrolithiasis renal tissues. S100A8 was strongly expressed in infiltrated leukocytes. Fibronectin was over-expressed in renal tubular cells. S100A8 and fibronectin were immunologically confirmed to exist in nephrolithiatic urine and stone matrix, but in healthy urine they were undetectable. Conclusion, both kidney stones and urine obtained from the same patients greatly contained inflammatory and fibrotic proteins. S100A8 and fibronectin were up-regulated in stone-baring kidneys and nephrolithiatic urine. Therefore, inflammation and fibrosis are suggested to be involved in the formation of kidney calculi.
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Affiliation(s)
- Chanchai Boonla
- Department of Biochemistry, Faculty of Medicine, Chulalongkorn University, Bangkok 10330 Thailand.
| | - Piyaratana Tosukhowong
- Department of Biochemistry, Faculty of Medicine, Chulalongkorn University, Bangkok 10330 Thailand
| | - Björn Spittau
- Department of Molecular Embryology, Institute for Anatomy and Cell Biology, University of Freiburg, 79104 Freiburg, Germany
| | - Andreas Schlosser
- Center for Biological Systems Analysis (ZBSA), Core Facility Proteomics, University of Freiburg, 79104 Freiburg, Germany
| | - Chaowat Pimratana
- Division of Urological Surgery, Khon Kaen Hospital, Khon Kaen 40000 Thailand
| | - Kerstin Krieglstein
- Department of Molecular Embryology, Institute for Anatomy and Cell Biology, University of Freiburg, 79104 Freiburg, Germany.
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1508
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Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins. Nat Methods 2013; 11:149-55. [PMID: 24317253 PMCID: PMC3922286 DOI: 10.1038/nmeth.2763] [Citation(s) in RCA: 150] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2013] [Accepted: 10/15/2013] [Indexed: 02/07/2023]
Abstract
Multiple reaction monitoring (MRM) mass spectrometry has been successfully applied to monitor targeted proteins in biological specimens, raising the possibility that assays could be configured to measure all human proteins. We report the results of a pilot study designed to test the feasibility of a large-scale, international effort for MRM assay generation. We have configured, validated across three laboratories and made publicly available as a resource to the community 645 novel MRM assays representing 319 proteins expressed in human breast cancer. Assays were multiplexed in groups of >150 peptides and deployed to quantify endogenous analytes in a panel of breast cancer-related cell lines. The median assay precision was 5.4%, with high interlaboratory correlation (R(2) > 0.96). Peptide measurements in breast cancer cell lines were able to discriminate among molecular subtypes and identify genome-driven changes in the cancer proteome. These results establish the feasibility of a large-scale effort to develop an MRM assay resource.
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1509
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Kao L, Wang YT, Chen YC, Tseng SF, Jhang JC, Chen YJ, Teng SC. Global analysis of cdc14 dephosphorylation sites reveals essential regulatory role in mitosis and cytokinesis. Mol Cell Proteomics 2013; 13:594-605. [PMID: 24319056 DOI: 10.1074/mcp.m113.032680] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Degradation of the M phase cyclins triggers the exit from M phase. Cdc14 is the major phosphatase required for the exit from the M phase. One of the functions of Cdc14 is to dephosphorylate and activate the Cdh1/APC/C complex, resulting in the degradation of the M phase cyclins. However, other crucial targets of Cdc14 for mitosis and cytokinesis remain to be elucidated. Here we systematically analyzed the positions of dephosphorylation sites for Cdc14 in the budding yeast Saccharomyces cerevisiae. Quantitative mass spectrometry identified a total of 835 dephosphorylation sites on 455 potential Cdc14 substrates in vivo. We validated two events, and through functional studies we discovered that Cdc14-mediated dephosphorylation of Smc4 and Bud3 is essential for proper mitosis and cytokinesis, respectively. These results provide insight into the Cdc14-mediated pathways for exiting the M phase.
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Affiliation(s)
- Li Kao
- Department of Microbiology, College of Medicine, National Taiwan University, Taipei 10051, Taiwan
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1510
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PAPE (Prefractionation-Assisted Phosphoprotein Enrichment): A Novel Approach for Phosphoproteomic Analysis of Green Tissues from Plants. Proteomes 2013; 1:254-274. [PMID: 28250405 PMCID: PMC5302697 DOI: 10.3390/proteomes1030254] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2013] [Revised: 11/28/2013] [Accepted: 11/28/2013] [Indexed: 11/17/2022] Open
Abstract
Phosphorylation is an important post-translational protein modification with regulatory roles in diverse cellular signaling pathways. Despite recent advances in mass spectrometry, the detection of phosphoproteins involved in signaling is still challenging, as protein phosphorylation is typically transient and/or occurs at low levels. In green plant tissues, the presence of highly abundant proteins, such as the subunits of the RuBisCO complex, further complicates phosphoprotein analysis. Here, we describe a simple, but powerful, method, which we named prefractionation-assisted phosphoprotein enrichment (PAPE), to increase the yield of phosphoproteins from Arabidopsis thaliana leaf material. The first step, a prefractionation via ammonium sulfate precipitation, not only depleted RuBisCO almost completely, but, serendipitously, also served as an efficient phosphoprotein enrichment step. When coupled with a subsequent metal oxide affinity chromatography (MOAC) step, the phosphoprotein content was highly enriched. The reproducibility and efficiency of phosphoprotein enrichment was verified by phospho-specific staining and, further, by mass spectrometry, where it could be shown that the final PAPE fraction contained a significant number of known and additionally novel (potential) phosphoproteins. Hence, this facile two-step procedure is a good prerequisite to probe the phosphoproteome and gain deeper insight into plant phosphorylation-based signaling events.
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1511
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Carlson SM, Moore KE, Green EM, Martín GM, Gozani O. Proteome-wide enrichment of proteins modified by lysine methylation. Nat Protoc 2013; 9:37-50. [PMID: 24309976 DOI: 10.1038/nprot.2013.164] [Citation(s) in RCA: 69] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
We present a protocol for using the triple malignant brain tumor domains of L3MBTL1 (3xMBT), which bind to mono- and di-methylated lysine with minimal sequence specificity, in order to enrich for such methylated lysine from cell lysates. Cells in culture are grown with amino acids containing light or heavy stable isotopic labels. Methylated proteins are enriched by incubating cell lysates with 3xMBT, or with the binding-null D355N mutant as a negative control. Quantitative liquid chromatography and tandem mass spectrometry (LC-MS/MS) are then used to identify proteins that are specifically enriched by 3xMBT pull-down. The addition of a third isotopic label allows the comparison of protein lysine methylation between different biological conditions. Unlike most approaches, our strategy does not require a prior hypothesis of candidate methylated proteins, and it recognizes a wider range of methylated proteins than any available method using antibodies. Cells are prepared by growing in isotopic labeling medium for about 7 d; the process of enriching methylated proteins takes 3 d and analysis by LC-MS/MS takes another 1-2 d.
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Affiliation(s)
- Scott M Carlson
- 1] Department of Biology, Stanford University, Stanford, California, USA. [2]
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1512
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Horvatovich P, Franke L, Bischoff R. Proteomic studies related to genetic determinants of variability in protein concentrations. J Proteome Res 2013; 13:5-14. [PMID: 24237071 DOI: 10.1021/pr400765y] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Genetic variation has multiple effects on the proteome. It may influence the expression level of proteins, modify their sequences through single nucleotide polymorphisms, the occurrence of allelic variants, or alternative splicing (ASP) events. This perspective paper summarizes the major effects of genetic variability on protein expression and isoforms and provides an overview of proteomics techniques and methods that allow studying the effects of genetic variability at different levels of the proteome. The paper provides an overview of recent quantitative trait loci studies performed to explore the effect of genetic variation on protein expression (pQTL). Finally it gives a perspective view on advances in proteomics technology and the role of the Chromosome-Centric Human Proteome Project (C-HPP) by creating large-scale resources that may facilitate performing more comprehensive pQTL experiments in the future.
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Affiliation(s)
- Péter Horvatovich
- Analytical Biochemistry, Department of Pharmacy, University of Groningen , A. Deusinglaan 1, 9713 AV Groningen, The Netherlands
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1513
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de la Tour CB, Passot FM, Toueille M, Mirabella B, Guérin P, Blanchard L, Servant P, de Groot A, Sommer S, Armengaud J. Comparative proteomics reveals key proteins recruited at the nucleoid of Deinococcus after irradiation-induced DNA damage. Proteomics 2013; 13:3457-69. [PMID: 24307635 DOI: 10.1002/pmic.201300249] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2013] [Revised: 10/19/2013] [Accepted: 10/23/2013] [Indexed: 11/09/2022]
Abstract
The nucleoids of radiation-resistant Deinococcus species show a high degree of compaction maintained after ionizing irradiation. We identified proteins recruited after irradiation in nucleoids of Deinococcus radiodurans and Deinococcus deserti by means of comparative proteomics. Proteins in nucleoid-enriched fractions from unirradiated and irradiated Deinococcus were identified and semiquantified by shotgun proteomics. The ssDNA-binding protein SSB, DNA gyrase subunits GyrA and GyrB, DNA topoisomerase I, RecA recombinase, UvrA excinuclease, RecQ helicase, DdrA, DdrB, and DdrD proteins were found in significantly higher amounts in irradiated nucleoids of both Deinococcus species. We observed, by immunofluorescence microscopy, the subcellular localization of these proteins in D. radiodurans, showing for the first time the recruitment of the DdrD protein into the D. radiodurans nucleoid. We specifically followed the kinetics of recruitment of RecA, DdrA, and DdrD to the nucleoid after irradiation. Remarkably, RecA proteins formed irregular filament-like structures 1 h after irradiation, before being redistributed throughout the cells by 3 h post-irradiation. Comparable dynamics of DdrD localization were observed, suggesting a possible functional interaction between RecA and DdrD. Several proteins involved in nucleotide synthesis were also seen in higher quantities in the nucleoids of irradiated cells, indicative of the existence of a mechanism for orchestrating the presence of proteins involved in DNA metabolism in nucleoids in response to massive DNA damage. All MS data have been deposited in the ProteomeXchange with identifier PXD00196 (http://proteomecentral.proteomexchange.org/dataset/PXD000196).
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1514
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Gu Q, Yu LR. Proteomics quality and standard: from a regulatory perspective. J Proteomics 2013; 96:353-9. [PMID: 24316359 DOI: 10.1016/j.jprot.2013.11.024] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2012] [Revised: 11/07/2013] [Accepted: 11/22/2013] [Indexed: 12/30/2022]
Abstract
Proteomics has emerged as a rapidly expanding field dealing with large-scale protein analyses. It is anticipated that proteomics data will be increasingly submitted to the U.S. Food and Drug Administration (FDA) for biomarker qualification or in conjunction with applications for the approval of drugs, medical devices, and other FDA-regulated consumer products. To date, however, no established guideline has been available regarding the generation, submission and assessment of the quality of proteomics data that will be reviewed by regulatory agencies for decision making. Therefore, this commentary is aimed at provoking some thoughts and debates towards developing a framework which can guide future proteomics data submission. The ultimate goal is to establish quality control standards for proteomics data generation and evaluation, and to prepare government agencies such as the FDA to meet future obligations utilizing proteomics data to support regulatory decision.
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Affiliation(s)
- Qiang Gu
- Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, USA
| | - Li-Rong Yu
- Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, USA.
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1515
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Petryszak R, Burdett T, Fiorelli B, Fonseca NA, Gonzalez-Porta M, Hastings E, Huber W, Jupp S, Keays M, Kryvych N, McMurry J, Marioni JC, Malone J, Megy K, Rustici G, Tang AY, Taubert J, Williams E, Mannion O, Parkinson HE, Brazma A. Expression Atlas update--a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments. Nucleic Acids Res 2013; 42:D926-32. [PMID: 24304889 PMCID: PMC3964963 DOI: 10.1093/nar/gkt1270] [Citation(s) in RCA: 239] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of 'baseline' expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful 'contrasts', i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user.
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Affiliation(s)
- Robert Petryszak
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, CB10 1SD, UK
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1516
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Nanjappa V, Thomas JK, Marimuthu A, Muthusamy B, Radhakrishnan A, Sharma R, Ahmad Khan A, Balakrishnan L, Sahasrabuddhe NA, Kumar S, Jhaveri BN, Sheth KV, Kumar Khatana R, Shaw PG, Srikanth SM, Mathur PP, Shankar S, Nagaraja D, Christopher R, Mathivanan S, Raju R, Sirdeshmukh R, Chatterjee A, Simpson RJ, Harsha HC, Pandey A, Prasad TSK. Plasma Proteome Database as a resource for proteomics research: 2014 update. Nucleic Acids Res 2013; 42:D959-65. [PMID: 24304897 PMCID: PMC3965042 DOI: 10.1093/nar/gkt1251] [Citation(s) in RCA: 249] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization's (HUPO's) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10,546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.
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Affiliation(s)
- Vishalakshi Nanjappa
- Institute of Bioinformatics, International Technology Park, Bangalore 560 066, Karnataka, India, Amrita School of Biotechnology, Amrita University, Kollam 690 525, Kerala, India, Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605 014, India, Department of Biochemistry and Molecular Biology, Pondicherry University, Puducherry 605014, India, Department of Neurochemistry, National Institute of Mental Health and Neurosciences, Bangalore 560 022, Karnataka, India, Department of Biotechnology, Kuvempu University, Shankaraghatta 577 451, Karnataka, India, Government Medical College, Bhavnagar 364 001, Gujarat, India, Mahatma Gandhi Institute of Medical Sciences, Sevagram, Wardha 442 012, Maharashtra, India, The Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA, Department of Internal Medicine, Armed Forces Medical College, Pune 411 040, Maharashtra, India, Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore 560 022, Karnataka, India, Department of Biochemistry, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria 3084, Australia, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA, Department of Biological Chemistry, Johns Hopkins University, Baltimore, MD 21205, USA, Department of Oncology, Johns Hopkins University, Baltimore, MD 21205, USA and Department of Pathology, Johns Hopkins University, Baltimore, MD 21205, USA
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1517
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Sebastiana M, Figueiredo A, Monteiro F, Martins J, Franco C, Coelho AV, Vaz F, Simões T, Penque D, Pais MS, Ferreira S. A possible approach for gel-based proteomic studies in recalcitrant woody plants. SPRINGERPLUS 2013; 2:210. [PMID: 23724367 PMCID: PMC3663981 DOI: 10.1186/2193-1801-2-210] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2013] [Accepted: 04/04/2013] [Indexed: 12/26/2022]
Abstract
Woody plants are particularly difficult to investigate due to high phenolic, resin, and tannin contents and laborious sample preparation. In particular, protein isolation from woody plants for two-dimensional gel electrophoresis (2-DE) is challenging as secondary metabolites negatively interfere with protein extraction and separation. In this study, three protein extraction protocols, using TCA, phenol and ethanol as precipitation or extraction agents, were tested in order to select the more efficient for woody recalcitrant plant gel-based proteomics. Grapevine leaves, pine needles and cork oak ectomycorrhizal roots were used to represent woody plant species and tissues. The phenol protocol produced higher quality 2-DE gels, with increased number of resolved spots, better spot focusing and representation of all molecular mass and isoelectric point ranges tested. In order to test the compatibility of the phenol extracted proteomes with protein identification several spots were excised from the phenol gels and analyzed by mass spectrometry (MALDI-TOF/TOF). Regardless the incomplete genome/protein databases for the plant species under analysis, 49 proteins were identified by Peptide Mass Fingerprint (PMF). Proteomic data have been deposited to the ProteomeXchange with identifier PXD000224. Our results demonstrate the complexity of protein extraction from woody plant tissues and the suitability of the phenol protocol for obtaining high quality protein extracts for efficient 2-DE separation and downstream applications such as protein identification by mass spectrometry.
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Affiliation(s)
- Mónica Sebastiana
- />Plant Systems Biology Lab, Center of Biodiversity, Functional & Integrative Genomics (BioFIG), Science Faculty of Lisbon University, Lisbon, 1749-016 Portugal
| | - Andreia Figueiredo
- />Plant Systems Biology Lab, Center of Biodiversity, Functional & Integrative Genomics (BioFIG), Science Faculty of Lisbon University, Lisbon, 1749-016 Portugal
| | - Filipa Monteiro
- />Plant Systems Biology Lab, Center of Biodiversity, Functional & Integrative Genomics (BioFIG), Science Faculty of Lisbon University, Lisbon, 1749-016 Portugal
| | - Joana Martins
- />Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Av. da Republica, Oeiras, 2780-157 Portugal
| | - Catarina Franco
- />Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Av. da Republica, Oeiras, 2780-157 Portugal
| | - Ana Varela Coelho
- />Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa, Av. da Republica, Oeiras, 2780-157 Portugal
| | - Fátima Vaz
- />Laboratório de Proteómica, Departamento de Genética, Instituto Nacional de Saúde Dr. Ricardo Jorge INSA I.P, Lisbon, Portugal
| | - Tânia Simões
- />Laboratório de Proteómica, Departamento de Genética, Instituto Nacional de Saúde Dr. Ricardo Jorge INSA I.P, Lisbon, Portugal
| | - Deborah Penque
- />Laboratório de Proteómica, Departamento de Genética, Instituto Nacional de Saúde Dr. Ricardo Jorge INSA I.P, Lisbon, Portugal
| | - Maria Salomé Pais
- />Plant Systems Biology Lab, Center of Biodiversity, Functional & Integrative Genomics (BioFIG), Science Faculty of Lisbon University, Lisbon, 1749-016 Portugal
| | - Sílvia Ferreira
- />Plant Systems Biology Lab, Center of Biodiversity, Functional & Integrative Genomics (BioFIG), Science Faculty of Lisbon University, Lisbon, 1749-016 Portugal
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1518
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Iglesias J, Trigueros M, Rojas-Triana M, Fernández M, Albar JP, Bustos R, Paz-Ares J, Rubio V. Proteomics identifies ubiquitin–proteasome targets and new roles for chromatin-remodeling in the Arabidopsis response to phosphate starvation. J Proteomics 2013; 94:1-22. [DOI: 10.1016/j.jprot.2013.08.015] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2013] [Revised: 07/30/2013] [Accepted: 08/14/2013] [Indexed: 11/29/2022]
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1519
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Wu W, Zhu Y, Ma Z, Sun Y, Quan Q, Li P, Hu P, Shi T, Lo C, Chu IK, Huang J. Proteomic evidence for genetic epistasis: ClpR4 mutations switch leaf variegation to virescence in Arabidopsis. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2013; 76:943-956. [PMID: 24124904 DOI: 10.1111/tpj.12344] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2013] [Revised: 09/26/2013] [Accepted: 10/01/2013] [Indexed: 05/28/2023]
Abstract
Chloroplast development in plants is regulated by a series of coordinated biological processes. In this work, a genetic suppressor screen for the leaf variegation phenotype of the thylakoid formation 1 (thf1) mutant combined with a proteomic assay was employed to elucidate this complicated network. We identified a mutation in ClpR4, named clpR4-3, which leads to leaf virescence and also rescues the var2 variegation. Proteomic analysis showed that the chloroplast proteome of clpR4-3 thf1 is dominantly controlled by clpR4-3, providing molecular mechanisms that cause genetic epistasis of clpR4-3 to thf1. Classification of the proteins significantly mis-regulated in the mutants revealed that those functioning in the expression of plastid genes are oppositely regulated while proteins functioning in antioxidative stress, protein folding, and starch metabolism are changed in the same direction between thf1 and clpR4-3. The levels of FtsHs including FtsH2/VAR2, FtsH8, and FtsH5/VAR1 are greatly reduced in thf1 compared with those in the wild type, but are higher in clpR4-3 thf1 than in thf1. Quantitative PCR analysis revealed that FtsH expression in clpR4-3 thf1 is regulated post-transcriptionally. In addition, a number of ribosomal proteins are less expressed in the clpR4-3 proteome, which is in line with the reduced levels of rRNAs in clpR4-3. Furthermore, knocking out PRPL11, one of the most downregulated proteins in the clpR4-3 thf1 proteome, rescues the leaf variegation phenotype of the thf1 and var2 mutants. These results provide insights into molecular mechanisms by which the virescent clpR4-3 mutation suppresses leaf variegation of thf1 and var2.
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Affiliation(s)
- Wenjuan Wu
- National Key Laboratory of Plant Molecular Genetics, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China
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1520
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Suski M, Olszanecki R, Stachowicz A, Madej J, Bujak-Giżycka B, Okoń K, Korbut R. The influence of angiotensin-(1–7) Mas receptor agonist (AVE 0991) on mitochondrial proteome in kidneys of apoE knockout mice. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2013; 1834:2463-9. [DOI: 10.1016/j.bbapap.2013.08.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2013] [Accepted: 08/19/2013] [Indexed: 12/18/2022]
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1521
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Zanivan S, Maione F, Hein MY, Hernández-Fernaud JR, Ostasiewicz P, Giraudo E, Mann M. SILAC-based proteomics of human primary endothelial cell morphogenesis unveils tumor angiogenic markers. Mol Cell Proteomics 2013; 12:3599-611. [PMID: 23979707 PMCID: PMC3861710 DOI: 10.1074/mcp.m113.031344] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2013] [Revised: 07/21/2013] [Indexed: 02/04/2023] Open
Abstract
Proteomics has been successfully used for cell culture on dishes, but more complex cellular systems have proven to be challenging and so far poorly approached with proteomics. Because of the complexity of the angiogenic program, we still do not have a complete understanding of the molecular mechanisms involved in this process, and there have been no in depth quantitative proteomic studies. Plating endothelial cells on matrigel recapitulates aspects of vessel growth, and here we investigate this mechanism by using a spike-in SILAC quantitative proteomic approach. By comparing proteomic changes in primary human endothelial cells morphogenesis on matrigel to general adhesion mechanisms in cells spreading on culture dish, we pinpoint pathways and proteins modulated by endothelial cells. The cell-extracellular matrix adhesion proteome depends on the adhesion substrate, and a detailed proteomic profile of the extracellular matrix secreted by endothelial cells identified CLEC14A as a matrix component, which binds to MMRN2. We verify deregulated levels of these proteins during tumor angiogenesis in models of multistage carcinogenesis. This is the most in depth quantitative proteomic study of endothelial cell morphogenesis, which shows the potential of applying high accuracy quantitative proteomics to in vitro models of vessel growth to shed new light on mechanisms that accompany pathological angiogenesis. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000359.
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MESH Headings
- Animals
- Antigens, Surface/genetics
- Antigens, Surface/metabolism
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Carbon Isotopes
- Cell Adhesion
- Cell Adhesion Molecules/genetics
- Cell Adhesion Molecules/metabolism
- Cell Differentiation
- Cell Transformation, Neoplastic/genetics
- Cell Transformation, Neoplastic/metabolism
- Cell Transformation, Neoplastic/pathology
- Collagen/chemistry
- Drug Combinations
- Extracellular Matrix/chemistry
- Extracellular Matrix/genetics
- Extracellular Matrix/metabolism
- Gene Expression Regulation, Neoplastic
- Human Umbilical Vein Endothelial Cells/metabolism
- Human Umbilical Vein Endothelial Cells/pathology
- Humans
- Isotope Labeling
- Laminin/chemistry
- Lectins, C-Type/genetics
- Lectins, C-Type/metabolism
- Mass Spectrometry
- Membrane Glycoproteins/genetics
- Membrane Glycoproteins/metabolism
- Mice
- Morphogenesis/genetics
- Neovascularization, Pathologic
- Primary Cell Culture
- Protein Binding
- Proteoglycans/chemistry
- Proteomics
- Signal Transduction
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Affiliation(s)
- Sara Zanivan
- From the ‡Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
- §The Beatson Institute for Cancer Research, Glasgow G61 1BD, United Kingdom
| | - Federica Maione
- ¶Laboratory of Transgenic Mouse Models, Institute for Cancer Research at Candiolo (IRCC), 10060 Candiolo, Italy
- ‖Department of Science and Drug Technology, University of Torino, 10125, Torino, Italy
| | - Marco Y. Hein
- From the ‡Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | | | - Pawel Ostasiewicz
- From the ‡Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
- **Department of Pathology, Wroclaw Medical University, 50-368, Wroclaw, Poland
| | - Enrico Giraudo
- ¶Laboratory of Transgenic Mouse Models, Institute for Cancer Research at Candiolo (IRCC), 10060 Candiolo, Italy
- ‖Department of Science and Drug Technology, University of Torino, 10125, Torino, Italy
| | - Matthias Mann
- From the ‡Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
- ‡‡The Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
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1522
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Kumar S, Kumar K, Pandey P, Rajamani V, Padmalatha KV, Dhandapani G, Kanakachari M, Leelavathi S, Kumar PA, Reddy VS. Glycoproteome of elongating cotton fiber cells. Mol Cell Proteomics 2013; 12:3677-89. [PMID: 24019148 PMCID: PMC3861716 DOI: 10.1074/mcp.m113.030726] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2013] [Revised: 09/04/2013] [Indexed: 11/21/2022] Open
Abstract
Cotton ovule epidermal cell differentiation into long fibers primarily depends on wall-oriented processes such as loosening, elongation, remodeling, and maturation. Such processes are governed by cell wall bound structural proteins and interacting carbohydrate active enzymes. Glycosylation plays a major role in the structural, functional, and localization aspects of the cell wall and extracellular destined proteins. Elucidating the glycoproteome of fiber cells would reflect its wall composition as well as compartmental requirement, which must be system specific. Following complementary proteomic approaches, we have identified 334 unique proteins comprising structural and regulatory families. Glycopeptide-based enrichment followed by deglycosylation with PNGase F and A revealed 92 unique peptides containing 106 formerly N-linked glycosylated sites from 67 unique proteins. Our results showed that structural proteins like arabinogalactans and carbohydrate active enzymes were relatively more abundant and showed stage- and isoform-specific expression patterns in the differentiating fiber cell. Furthermore, our data also revealed the presence of heterogeneous and novel forms of structural and regulatory glycoproteins. Comparative analysis with other plant glycoproteomes highlighted the unique composition of the fiber glycoproteome. The present study provides the first insight into the identity, abundance, diversity, and composition of the glycoproteome within single celled cotton fibers. The elucidated composition also indirectly provides clues about unicellular compartmental requirements underlying single cell differentiation.
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Affiliation(s)
- Saravanan Kumar
- From the ‡Plant Transformation Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | - Krishan Kumar
- From the ‡Plant Transformation Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | - Pankaj Pandey
- From the ‡Plant Transformation Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | - Vijayalakshmi Rajamani
- From the ‡Plant Transformation Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | | | - Gurusamy Dhandapani
- §National Research Centre on Plant Biotechnology (NRCPB), IARI, New Delhi, India
| | | | - Sadhu Leelavathi
- From the ‡Plant Transformation Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | | | - Vanga Siva Reddy
- From the ‡Plant Transformation Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
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1523
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Kolker E, Özdemir V, Martens L, Hancock W, Anderson G, Anderson N, Aynacioglu S, Baranova A, Campagna SR, Chen R, Choiniere J, Dearth SP, Feng WC, Ferguson L, Fox G, Frishman D, Grossman R, Heath A, Higdon R, Hutz MH, Janko I, Jiang L, Joshi S, Kel A, Kemnitz JW, Kohane IS, Kolker N, Lancet D, Lee E, Li W, Lisitsa A, Llerena A, MacNealy-Koch C, Marshall JC, Masuzzo P, May A, Mias G, Monroe M, Montague E, Mooney S, Nesvizhskii A, Noronha S, Omenn G, Rajasimha H, Ramamoorthy P, Sheehan J, Smarr L, Smith CV, Smith T, Snyder M, Rapole S, Srivastava S, Stanberry L, Stewart E, Toppo S, Uetz P, Verheggen K, Voy BH, Warnich L, Wilhelm SW, Yandl G. Toward More Transparent and Reproducible Omics Studies Through a Common Metadata Checklist and Data Publications. BIG DATA 2013; 1:196-201. [PMID: 27447251 DOI: 10.1089/big.2013.0039] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Biological processes are fundamentally driven by complex interactions between biomolecules. Integrated high-throughput omics studies enable multifaceted views of cells, organisms, or their communities. With the advent of new post-genomics technologies, omics studies are becoming increasingly prevalent; yet the full impact of these studies can only be realized through data harmonization, sharing, meta-analysis, and integrated research. These essential steps require consistent generation, capture, and distribution of metadata. To ensure transparency, facilitate data harmonization, and maximize reproducibility and usability of life sciences studies, we propose a simple common omics metadata checklist. The proposed checklist is built on the rich ontologies and standards already in use by the life sciences community. The checklist will serve as a common denominator to guide experimental design, capture important parameters, and be used as a standard format for stand-alone data publications. The omics metadata checklist and data publications will create efficient linkages between omics data and knowledge-based life sciences innovation and, importantly, allow for appropriate attribution to data generators and infrastructure science builders in the post-genomics era. We ask that the life sciences community test the proposed omics metadata checklist and data publications and provide feedback for their use and improvement.
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Affiliation(s)
- Eugene Kolker
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 2 Predictive Analytics , Seattle Children's, Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
| | - Vural Özdemir
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 4 Office of the President, Gaziantep University , International Affairs and Global Development Strategy
- 5 Faculty of Communications, Universite Bulvarı , Kilis Yolu, Turkey
| | - Lennart Martens
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 6 Department of Medical Protein Research, Vlaams Instituut voor Biotechnologie , Ghent, Belgium
- 7 Department of Biochemistry, Ghent University, Ghent , Belgium
| | - William Hancock
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 8 Department of Chemistry, Barnett Institute, Northeastern University , Boston, Massachusetts
| | - Gordon Anderson
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 9 Fundamental & Computational Sciences Directorate, Pacific Northwest National Laboratory , Richland, Washington
| | - Nathaniel Anderson
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
| | - Sukru Aynacioglu
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 10 Department of Pharmacology, Gaziantep University , Gaziantep, Turkey
| | - Ancha Baranova
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 11 School of Systems Biology, George Mason University , Manassas, Virginia
| | - Shawn R Campagna
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 12 Department of Chemistry, University of Tennessee Knoxville , Knoxville, Tennessee
| | - Rui Chen
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 13 Department of Genetics, Stanford University , Stanford, California
| | - John Choiniere
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
| | - Stephen P Dearth
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 12 Department of Chemistry, University of Tennessee Knoxville , Knoxville, Tennessee
| | - Wu-Chun Feng
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 14 Department of Computer Science, Virginia Tech, Blacksburg Virginia
- 15 Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg Virginia
- 16 SyNeRGy Laboratory, Virginia Tech, Blacksburg, Virginia
| | - Lynnette Ferguson
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 17 Department of Nutrition, Auckland Cancer Society Research Centre, University of Auckland , Auckland, New Zealand
| | - Geoffrey Fox
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 18 School of Informatics and Computing, Indiana University , Bloomington, Indiana
| | - Dmitrij Frishman
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 19 Technische Universitat Munchen , Wissenshaftzentrum Weihenstephan, Freising, Germany
| | - Robert Grossman
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 20 Institute for Genomics and Systems Biology, University of Chicago , Chicago Illinois
- 21 Department of Medicine, University of Chicago , Chicago, Illinois
| | - Allison Heath
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 20 Institute for Genomics and Systems Biology, University of Chicago , Chicago Illinois
- 22 Knapp Center for Biomedical Discovery, University of Chicago , Chicago, Illinois
| | - Roger Higdon
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 2 Predictive Analytics , Seattle Children's, Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
| | - Mara H Hutz
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 23 Departamento de Genetica, Instituto de Biociencias, Federal University of Rio Grande do Sul , Porto Alegre, Brazil
| | - Imre Janko
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 24 High-Throughput Analysis Core, Seattle Children's Research Institute , Seattle, Washington
| | - Lihua Jiang
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 13 Department of Genetics, Stanford University , Stanford, California
| | - Sanjay Joshi
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 25 Life Sciences , EMC, Hopkinton, Massachusetts
| | - Alexander Kel
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 26 GeneXplain GmbH , Wolfenbüttel, Germany
| | - Joseph W Kemnitz
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 27 Department of Cell and Regenerative Biology, University of Wisconsin-Madison , Madison, Wisconsin
- 28 Wisconsin National Primate Research Center, University of Wisconsin-Madison , Madison, Wisconsin
| | - Isaac S Kohane
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 29 Pediatrics and Health Sciences Technology, Children's Hospital and Harvard Medical School , Boston, Massachusetts
- 30 HMS Center for Biomedical Informatics, Countway Library of Medicine , Boston, Massachusetts
| | - Natali Kolker
- 2 Predictive Analytics , Seattle Children's, Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 24 High-Throughput Analysis Core, Seattle Children's Research Institute , Seattle, Washington
| | - Doron Lancet
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 31 Department of Molecular Genetics, Crown Human Genome Center , Weizmann Institute of Science, Rehovot, Israel
| | - Elaine Lee
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 24 High-Throughput Analysis Core, Seattle Children's Research Institute , Seattle, Washington
| | - Weizhong Li
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 32 Center for Research in Biological Systems, University of California , San Diego, La Jolla, California
| | - Andrey Lisitsa
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 33 Russian Human Proteome Organization (RHUPO) , Moscow, Russia
- 34 Institute of Biomedical Chemistry , Moscow, Russia
| | - Adrian Llerena
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 35 Clinical Research Center, Extremadura University Hospital and Medical School , Badajoz, Spain
| | - Courtney MacNealy-Koch
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
| | - Jean-Claude Marshall
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 36 Center for Translational Research, Catholic Health Initiatives , Towson, Maryland
| | - Paola Masuzzo
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 6 Department of Medical Protein Research, Vlaams Instituut voor Biotechnologie , Ghent, Belgium
- 7 Department of Biochemistry, Ghent University, Ghent , Belgium
| | - Amanda May
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 12 Department of Chemistry, University of Tennessee Knoxville , Knoxville, Tennessee
| | - George Mias
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 13 Department of Genetics, Stanford University , Stanford, California
| | - Matthew Monroe
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 37 Biological Sciences Division, Pacific Northwest National Laboratory , Richland, Washington
| | - Elizabeth Montague
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 2 Predictive Analytics , Seattle Children's, Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
| | - Sean Mooney
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 38 The Buck Institute for Research on Aging , Novato, California
| | - Alexey Nesvizhskii
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 39 Department of Pathology, University of Michigan , Ann Arbor, Michigan
- 40 Computational Medicine and Bioinformatics, University of Michigan , Ann Arbor, Michigan
| | - Santosh Noronha
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 41 Department of Chemical Engineering, Indian Institute of Technology Bombay , Powai, Mumbai, India
| | - Gilbert Omenn
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 42 Center for Computational Medicine and Bioinformatics, University of Michigan , Ann Arbor, Michigan
- 43 Departments of Molecular Medicine & Genetics and Human Genetics, University of Michigan , Ann Arbor Michigan
- 44 Department of Computational Medicine and Bioinformatics, University of Michigan , Ann Arbor, Michigan
- 45 School of Public Health, University of Michigan , Ann Arbor, Michigan
| | - Harsha Rajasimha
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 46 J eeva Informatics Solutions LLC , Derwood, Maryland
| | - Preveen Ramamoorthy
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 47 Molecular Diagnostics Department, National Jewish Health , Denver Colorado
| | - Jerry Sheehan
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 48 California Institute for Telecommunications and Information Technology, University of California-San Diego , La Jolla, California
| | - Larry Smarr
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 48 California Institute for Telecommunications and Information Technology, University of California-San Diego , La Jolla, California
| | - Charles V Smith
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 49 Center for Developmental Therapeutics, Seattle Children's Research Institute , Seattle, Washington
| | - Todd Smith
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 50 Digital World Biology , Seattle, Washington
| | - Michael Snyder
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 13 Department of Genetics, Stanford University , Stanford, California
- 51 Stanford Center for Genomics and Personalized Medicine, Stanford University , Stanford, California
| | - Srikanth Rapole
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 52 Proteomics Laboratory, National Centre for Cell Science, University of Pune , Pune, India
| | - Sanjeeva Srivastava
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 53 Proteomics Laboratory, Indian Institute of Technology Bombay , Mumbai, India
| | - Larissa Stanberry
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 2 Predictive Analytics , Seattle Children's, Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
| | - Elizabeth Stewart
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
| | - Stefano Toppo
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 54 Department of Molecular Medicine, University of Padova , Padova, Italy
| | - Peter Uetz
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 55 Center for the Study of Biological Complexity (CSBC), Virginia Commonwealth University , Richmond, Virginia
| | - Kenneth Verheggen
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 6 Department of Medical Protein Research, Vlaams Instituut voor Biotechnologie , Ghent, Belgium
- 7 Department of Biochemistry, Ghent University, Ghent , Belgium
| | - Brynn H Voy
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 56 Department of Animal Science, University of Tennessee Institute of Agriculture , Knoxville, Tennessee
| | - Louise Warnich
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 57 Department of Genetics, Faculty of AgriSciences, University of Stellenbosch , Stellenbosch, South Africa
| | - Steven W Wilhelm
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
- 58 Department of Microbiology, University of Tennessee-Knoxville , Knoxville, Tennessee
| | - Gregory Yandl
- 1 Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute , Seattle, Washington
- 3 Data-Enabled Life Sciences Alliance (DELSA Global) , Seattle, Washington
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1524
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Jüschke C, Dohnal I, Pichler P, Harzer H, Swart R, Ammerer G, Mechtler K, Knoblich JA. Transcriptome and proteome quantification of a tumor model provides novel insights into post-transcriptional gene regulation. Genome Biol 2013; 14:r133. [PMID: 24289286 PMCID: PMC4053992 DOI: 10.1186/gb-2013-14-11-r133] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2013] [Accepted: 11/30/2013] [Indexed: 11/25/2022] Open
Abstract
Background Genome‐wide transcriptome analyses have given systems‐level insights into gene regulatory networks. Due to the limited depth of quantitative proteomics, however, our understanding of post‐transcriptional gene regulation and its effects on protein‐complex stoichiometry are lagging behind. Results Here, we employ deep sequencing and the isobaric tag for relative and absolute quantification (iTRAQ) technology to determine transcript and protein expression changes of a Drosophila brain tumor model at near genome‐wide resolution. In total, we quantify more than 6,200 tissue‐specific proteins, corresponding to about 70% of all transcribed protein‐coding genes. Using our integrated data set, we demonstrate that post‐transcriptional gene regulation varies considerably with biological function and is surprisingly high for genes regulating transcription. We combine our quantitative data with protein‐protein interaction data and show that post‐transcriptional mechanisms significantly enhance co‐regulation of protein‐complex subunits beyond transcriptional co‐regulation. Interestingly, our results suggest that only about 11% of the annotated Drosophila protein complexes are co‐regulated in the brain. Finally, we refine the composition of some of these core protein complexes by analyzing the co‐regulation of potential subunits. Conclusions Our comprehensive transcriptome and proteome data provide a valuable resource for quantitative biology and offer novel insights into understanding post‐transcriptional gene regulation in a tumor model.
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1525
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Liu H, Zhang H, Niedzwiedzki DM, Prado M, He G, Gross ML, Blankenship RE. Phycobilisomes supply excitations to both photosystems in a megacomplex in cyanobacteria. Science 2013; 342:1104-7. [PMID: 24288334 PMCID: PMC3947847 DOI: 10.1126/science.1242321] [Citation(s) in RCA: 251] [Impact Index Per Article: 20.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
In photosynthetic organisms, photons are captured by light-harvesting antenna complexes, and energy is transferred to reaction centers where photochemical reactions take place. We describe here the isolation and characterization of a fully functional megacomplex composed of a phycobilisome antenna complex and photosystems I and II from the cyanobacterium Synechocystis PCC 6803. A combination of in vivo protein cross-linking, mass spectrometry, and time-resolved spectroscopy indicates that the megacomplex is organized to facilitate energy transfer but not intercomplex electron transfer, which requires diffusible intermediates and the cytochrome b6f complex. The organization provides a basis for understanding how phycobilisomes transfer excitation energy to reaction centers and how the energy balance of two photosystems is achieved, allowing the organism to adapt to varying ecophysiological conditions.
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Affiliation(s)
- Haijun Liu
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
- Photosynthetic Antenna Research Center, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Hao Zhang
- Photosynthetic Antenna Research Center, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Dariusz M. Niedzwiedzki
- Photosynthetic Antenna Research Center, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Mindy Prado
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
- Photosynthetic Antenna Research Center, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Guannan He
- Photosynthetic Antenna Research Center, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Michael L. Gross
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Robert E. Blankenship
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
- Photosynthetic Antenna Research Center, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO 63130, USA
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1526
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Bomans K, Lang A, Roedl V, Adolf L, Kyriosoglou K, Diepold K, Eberl G, Mølhøj M, Strauss U, Schmalz C, Vogel R, Reusch D, Wegele H, Wiedmann M, Bulau P. Identification and monitoring of host cell proteins by mass spectrometry combined with high performance immunochemistry testing. PLoS One 2013; 8:e81639. [PMID: 24312330 PMCID: PMC3842259 DOI: 10.1371/journal.pone.0081639] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2013] [Accepted: 10/15/2013] [Indexed: 11/19/2022] Open
Abstract
Biotherapeutics are often produced in non-human host cells like Escherichia coli, yeast, and various mammalian cell lines. A major focus of any therapeutic protein purification process is to reduce host cell proteins to an acceptable low level. In this study, various E. coli host cell proteins were identified at different purifications steps by HPLC fractionation, SDS-PAGE analysis, and tryptic peptide mapping combined with online liquid chromatography mass spectrometry (LC-MS). However, no host cell proteins could be verified by direct LC-MS analysis of final drug substance material. In contrast, the application of affinity enrichment chromatography prior to comprehensive LC-MS was adequate to identify several low abundant host cell proteins at the final drug substance level. Bacterial alkaline phosphatase (BAP) was identified as being the most abundant host cell protein at several purification steps. Thus, we firstly established two different assays for enzymatic and immunological BAP monitoring using the cobas® technology. By using this strategy we were able to demonstrate an almost complete removal of BAP enzymatic activity by the established therapeutic protein purification process. In summary, the impact of fermentation, purification, and formulation conditions on host cell protein removal and biological activity can be conducted by monitoring process-specific host cell proteins in a GMP-compatible and high-throughput (> 1000 samples/day) manner.
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Affiliation(s)
- Katrin Bomans
- Pharma Development, Roche Diagnostics GmbH, Penzberg, Germany
| | - Antje Lang
- Pharma Biotech, Roche Diagnostics GmbH, Penzberg, Germany
| | - Veronika Roedl
- Pharma Biotech, Roche Diagnostics GmbH, Penzberg, Germany
| | - Lisa Adolf
- Pharma Development, Roche Diagnostics GmbH, Penzberg, Germany
| | | | | | - Gabriele Eberl
- Pharma Biotech, Roche Diagnostics GmbH, Penzberg, Germany
| | - Michael Mølhøj
- Pharma Development, Roche Diagnostics GmbH, Penzberg, Germany
| | - Ulrike Strauss
- Pharma Biotech, Roche Diagnostics GmbH, Penzberg, Germany
| | | | - Rudolf Vogel
- Professional Diagnostics, Roche Diagnostics GmbH, Penzberg, Germany
| | - Dietmar Reusch
- Pharma Development, Roche Diagnostics GmbH, Penzberg, Germany
| | - Harald Wegele
- Pharma Development, Roche Diagnostics GmbH, Penzberg, Germany
| | | | - Patrick Bulau
- Pharma Development, Roche Diagnostics GmbH, Penzberg, Germany
- * E-mail:
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1527
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Fierro-Monti I, Echeverria P, Racle J, Hernandez C, Picard D, Quadroni M. Dynamic impacts of the inhibition of the molecular chaperone Hsp90 on the T-cell proteome have implications for anti-cancer therapy. PLoS One 2013; 8:e80425. [PMID: 24312219 PMCID: PMC3842317 DOI: 10.1371/journal.pone.0080425] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Accepted: 10/02/2013] [Indexed: 11/19/2022] Open
Abstract
The molecular chaperone Hsp90-dependent proteome represents a complex protein network of critical biological and medical relevance. Known to associate with proteins with a broad variety of functions termed clients, Hsp90 maintains key essential and oncogenic signalling pathways. Consequently, Hsp90 inhibitors are being tested as anti-cancer drugs. Using an integrated systematic approach to analyse the effects of Hsp90 inhibition in T-cells, we quantified differential changes in the Hsp90-dependent proteome, Hsp90 interactome, and a selection of the transcriptome. Kinetic behaviours in the Hsp90-dependent proteome were assessed using a novel pulse-chase strategy (Fierro-Monti et al., accompanying article), detecting effects on both protein stability and synthesis. Global and specific dynamic impacts, including proteostatic responses, are due to direct inhibition of Hsp90 as well as indirect effects. As a result, a decrease was detected in most proteins that changed their levels, including known Hsp90 clients. Most likely, consequences of the role of Hsp90 in gene expression determined a global reduction in net de novo protein synthesis. This decrease appeared to be greater in magnitude than a concomitantly observed global increase in protein decay rates. Several novel putative Hsp90 clients were validated, and interestingly, protein families with critical functions, particularly the Hsp90 family and cofactors themselves as well as protein kinases, displayed strongly increased decay rates due to Hsp90 inhibitor treatment. Remarkably, an upsurge in survival pathways, involving molecular chaperones and several oncoproteins, and decreased levels of some tumour suppressors, have implications for anti-cancer therapy with Hsp90 inhibitors. The diversity of global effects may represent a paradigm of mechanisms that are operating to shield cells from proteotoxic stress, by promoting pro-survival and anti-proliferative functions. Data are available via ProteomeXchange with identifier PXD000537.
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Affiliation(s)
- Ivo Fierro-Monti
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Pablo Echeverria
- Département de Biologie Cellulaire, Université de Genève, Genève, Switzerland
| | - Julien Racle
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Vital-IT Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Celine Hernandez
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
- Vital-IT Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Didier Picard
- Département de Biologie Cellulaire, Université de Genève, Genève, Switzerland
| | - Manfredo Quadroni
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
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1528
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Verheggen K, Barsnes H, Martens L. Distributed computing and data storage in proteomics: many hands make light work, and a stronger memory. Proteomics 2013; 14:367-77. [PMID: 24285552 DOI: 10.1002/pmic.201300288] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2013] [Revised: 09/09/2013] [Accepted: 09/23/2013] [Indexed: 12/25/2022]
Abstract
Modern day proteomics generates ever more complex data, causing the requirements on the storage and processing of such data to outgrow the capacity of most desktop computers. To cope with the increased computational demands, distributed architectures have gained substantial popularity in the recent years. In this review, we provide an overview of the current techniques for distributed computing, along with examples of how the techniques are currently being employed in the field of proteomics. We thus underline the benefits of distributed computing in proteomics, while also pointing out the potential issues and pitfalls involved.
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Affiliation(s)
- Kenneth Verheggen
- Department of Medical Protein Research, VIB, Ghent, Belgium; Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
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1529
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Low TY, van Heesch S, van den Toorn H, Giansanti P, Cristobal A, Toonen P, Schafer S, Hübner N, van Breukelen B, Mohammed S, Cuppen E, Heck AJR, Guryev V. Quantitative and qualitative proteome characteristics extracted from in-depth integrated genomics and proteomics analysis. Cell Rep 2013; 5:1469-78. [PMID: 24290761 DOI: 10.1016/j.celrep.2013.10.041] [Citation(s) in RCA: 94] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2013] [Revised: 09/28/2013] [Accepted: 10/24/2013] [Indexed: 02/07/2023] Open
Abstract
Quantitative and qualitative protein characteristics are regulated at genomic, transcriptomic, and posttranscriptional levels. Here, we integrated in-depth transcriptome and proteome analyses of liver tissues from two rat strains to unravel the interactions within and between these layers. We obtained peptide evidence for 26,463 rat liver proteins. We validated 1,195 gene predictions, 83 splice events, 126 proteins with nonsynonymous variants, and 20 isoforms with nonsynonymous RNA editing. Quantitative RNA sequencing and proteomics data correlate highly between strains but poorly among each other, indicating extensive nongenetic regulation. Our multilevel analysis identified a genomic variant in the promoter of the most differentially expressed gene Cyp17a1, a previously reported top hit in genome-wide association studies for human hypertension, as a potential contributor to the hypertension phenotype in SHR rats. These results demonstrate the power of and need for integrative analysis for understanding genetic control of molecular dynamics and phenotypic diversity in a system-wide manner.
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Affiliation(s)
- Teck Yew Low
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Sebastiaan van Heesch
- Hubrecht Institute-KNAW & University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
| | - Henk van den Toorn
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Piero Giansanti
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Alba Cristobal
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Pim Toonen
- Hubrecht Institute-KNAW & University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
| | - Sebastian Schafer
- Max-Delbruck-Center for Molecular Medicine (MDC), Robert-Rossle-Strasse 10, 13125 Berlin, Germany
| | - Norbert Hübner
- Max-Delbruck-Center for Molecular Medicine (MDC), Robert-Rossle-Strasse 10, 13125 Berlin, Germany; DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Bas van Breukelen
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Shabaz Mohammed
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 CH Utrecht, the Netherlands
| | - Edwin Cuppen
- Hubrecht Institute-KNAW & University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands.
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 CH Utrecht, the Netherlands.
| | - Victor Guryev
- Hubrecht Institute-KNAW & University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, the Netherlands
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1530
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Fierro-Monti I, Racle J, Hernandez C, Waridel P, Hatzimanikatis V, Quadroni M. A novel pulse-chase SILAC strategy measures changes in protein decay and synthesis rates induced by perturbation of proteostasis with an Hsp90 inhibitor. PLoS One 2013; 8:e80423. [PMID: 24312217 PMCID: PMC3842330 DOI: 10.1371/journal.pone.0080423] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2013] [Accepted: 10/02/2013] [Indexed: 11/18/2022] Open
Abstract
Standard proteomics methods allow the relative quantitation of levels of thousands of proteins in two or more samples. While such methods are invaluable for defining the variations in protein concentrations which follow the perturbation of a biological system, they do not offer information on the mechanisms underlying such changes. Expanding on previous work [1], we developed a pulse-chase (pc) variant of SILAC (stable isotope labeling by amino acids in cell culture). pcSILAC can quantitate in one experiment and for two conditions the relative levels of proteins newly synthesized in a given time as well as the relative levels of remaining preexisting proteins. We validated the method studying the drug-mediated inhibition of the Hsp90 molecular chaperone, which is known to lead to increased synthesis of stress response proteins as well as the increased decay of Hsp90 "clients". We showed that pcSILAC can give information on changes in global cellular proteostasis induced by treatment with the inhibitor, which are normally not captured by standard relative quantitation techniques. Furthermore, we have developed a mathematical model and computational framework that uses pcSILAC data to determine degradation constants kd and synthesis rates Vs for proteins in both control and drug-treated cells. The results show that Hsp90 inhibition induced a generalized slowdown of protein synthesis and an increase in protein decay. Treatment with the inhibitor also resulted in widespread protein-specific changes in relative synthesis rates, together with variations in protein decay rates. The latter were more restricted to individual proteins or protein families than the variations in synthesis. Our results establish pcSILAC as a viable workflow for the mechanistic dissection of changes in the proteome which follow perturbations. Data are available via ProteomeXchange with identifier PXD000538.
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Affiliation(s)
- Ivo Fierro-Monti
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Julien Racle
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Celine Hernandez
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
- SIB Swiss Institute of Bioinformatics, Vital-IT group, Lausanne, Switzerland
| | - Patrice Waridel
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Vassily Hatzimanikatis
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Manfredo Quadroni
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
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1531
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Schlage P, Egli FE, Nanni P, Wang LW, Kizhakkedathu JN, Apte SS, auf dem Keller U. Time-resolved analysis of the matrix metalloproteinase 10 substrate degradome. Mol Cell Proteomics 2013; 13:580-93. [PMID: 24281761 DOI: 10.1074/mcp.m113.035139] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Proteolysis is an irreversible post-translational modification that affects intra- and intercellular communication by modulating the activity of bioactive mediators. Key to understanding protease function is the system-wide identification of cleavage events and their dynamics in physiological contexts. Despite recent advances in mass spectrometry-based proteomics for high-throughput substrate screening, current approaches suffer from high false positive rates and only capture single states of protease activity. Here, we present a workflow based on multiplexed terminal amine isotopic labeling of substrates for time-resolved substrate degradomics in complex proteomes. This approach significantly enhances confidence in substrate identification and categorizes cleavage events by specificity and structural accessibility of the cleavage site. We demonstrate concomitant quantification of cleavage site spanning peptides and neo-N and/or neo-C termini to estimate relative ratios of noncleaved and cleaved forms of substrate proteins. By applying this strategy to dissect the matrix metalloproteinase 10 (MMP10) substrate degradome in fibroblast secretomes, we identified the extracellular matrix protein ADAMTS-like protein 1 (ADAMTSL1) as a direct MMP10 substrate and revealed MMP10-dependent ectodomain shedding of platelet-derived growth factor receptor alpha (PDGFRα) as well as sequential processing of type I collagen. The data have been deposited to the ProteomeXchange Consortium with identifier PXD000503.
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Affiliation(s)
- Pascal Schlage
- ETH Zurich, Department of Biology, Institute of Molecular Health Sciences, Schafmattstr. 22, 8093 Zurich, Switzerland
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1532
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Lourenço RF, Leme AFP, Oliveira CC. Proteomic Analysis of Yeast Mutant RNA Exosome Complexes. J Proteome Res 2013; 12:5912-22. [DOI: 10.1021/pr400972x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Rogério F. Lourenço
- Department
of Biochemistry, Chemistry Institute, University of São Paulo, Av. Prof. Lineu Prestes 748, 05508-000 São Paulo, Brazil
| | - Adriana F. P. Leme
- Mass
Spectrometry Laboratory, Brazilian Biosciences National Laboratory- CNPEM, R. Giuseppe Máximo Scolfaro 10000, 13083-970 Campinas, Brazil
| | - Carla C. Oliveira
- Department
of Biochemistry, Chemistry Institute, University of São Paulo, Av. Prof. Lineu Prestes 748, 05508-000 São Paulo, Brazil
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1533
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Önder Ö, Shao W, Kemps BD, Lam H, Brisson D. Identifying sources of tick blood meals using unidentified tandem mass spectral libraries. Nat Commun 2013; 4:1746. [PMID: 23612287 PMCID: PMC3635114 DOI: 10.1038/ncomms2730] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2012] [Accepted: 03/11/2013] [Indexed: 11/21/2022] Open
Abstract
Rapid and reliable identification of the vertebrate species on which a disease vector previously parasitized is imperative to study ecological factors that affect pathogen distribution and can aid the development of public health programs. Here we describe a proteome profiling technique designed to identify the source of blood meals of hematophagous arthropods. This method employs direct spectral matching and thus does not require a priori knowledge of any genetic or protein sequence information. Using this technology, we detect remnants of blood in blacklegged ticks (Ixodes scapularis) and correctly determine the vertebrate species from which the blood was derived even six months after the tick had fed. This biological fingerprinting methodology is sensitive, fast, cost-effective, and can potentially be adapted for other biological and medical applications when existing genome-based methods are impractical or ineffective.
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Affiliation(s)
- Özlem Önder
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19014-6019, USA
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1534
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Grolimund L, Aeby E, Hamelin R, Armand F, Chiappe D, Moniatte M, Lingner J. A quantitative telomeric chromatin isolation protocol identifies different telomeric states. Nat Commun 2013; 4:2848. [DOI: 10.1038/ncomms3848] [Citation(s) in RCA: 86] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2013] [Accepted: 10/31/2013] [Indexed: 01/08/2023] Open
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1535
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A perspective on proteomics in cell biology. Trends Cell Biol 2013; 24:257-64. [PMID: 24284280 PMCID: PMC3989996 DOI: 10.1016/j.tcb.2013.10.010] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2013] [Revised: 10/14/2013] [Accepted: 10/30/2013] [Indexed: 12/21/2022]
Abstract
Proteomic strategies facilitate system-wide analyses of protein complexes. Isotope labelling allows quantitative measurement of protein properties, not only their identification. There is a major need to organise effective community sharing of the proteomic data mountain. The integration of proteomic data with other online data repositories must be improved.
During the past 15 years mass spectrometry (MS)-based analyses have become established as the method of choice for direct protein identification and measurement. Owing to the remarkable improvements in the sensitivity and resolution of MS instruments, this technology has revolutionised the opportunities available for the system-wide characterisation of proteins, with wide applications across virtually the whole of cell biology. In this article we provide a perspective on the current state of the art and discuss how the future of cell biology research may benefit from further developments and applications in the field of MS and proteomics, highlighting the major challenges ahead for the community in organising the effective sharing and integration of the resulting data mountain.
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1536
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Pollo-Oliveira L, Post H, Acencio ML, Lemke N, van den Toorn H, Tragante V, Heck AJR, Altelaar AFM, Yatsuda AP. Unravelling the Neospora caninum secretome through the secreted fraction (ESA) and quantification of the discharged tachyzoite using high-resolution mass spectrometry-based proteomics. Parasit Vectors 2013; 6:335. [PMID: 24267406 PMCID: PMC4182915 DOI: 10.1186/1756-3305-6-335] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2013] [Accepted: 11/15/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The apicomplexan parasite Neospora caninum causes neosporosis, a disease that leads to abortion or stillbirth in cattle, generating an economic impact on the dairy and beef cattle trade. As an obligatory intracellular parasite, N. caninum needs to invade the host cell in an active manner to survive. The increase in parasite cytosolic Ca2+ upon contact with the host cell mediates critical events, including the exocytosis of phylum-specific secretory organelles and the activation of the parasite invasion motor. Because invasion is considered a requirement for pathogen survival and replication within the host, the identification of secreted proteins (secretome) involved in invasion may be useful to reveal interesting targets for therapeutic intervention. METHODS To chart the currently missing N. caninum secretome, we employed mass spectrometry-based proteomics to identify proteins present in the N. caninum tachyzoite using two different approaches. The first approach was identifying the proteins present in the tachyzoite-secreted fraction (ESA). The second approach was determining the relative quantification through peptide stable isotope labelling of the tachyzoites submitted to an ethanol secretion stimulus (discharged tachyzoite), expecting to identify the secreted proteins among the down-regulated group. RESULTS As a result, 615 proteins were identified at ESA and 2,011 proteins quantified at the discharged tachyzoite. We have analysed the connection between the secreted and the down-regulated proteins and searched for putative regulators of the secretion process among the up-regulated proteins. An interaction network was built by computational prediction involving the up- and down-regulated proteins. The mass spectrometry proteomics data have been deposited to the ProteomeXchange with identifier PXD000424. CONCLUSIONS The comparison between the protein abundances in ESA and their measure in the discharged tachyzoite allowed for a more precise identification of the most likely secreted proteins. Information from the network interaction and up-regulated proteins was important to recognise key proteins potentially involved in the metabolic regulation of secretion. Our results may be helpful to guide the selection of targets to be investigated against Neospora caninum and other Apicomplexan organisms.
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Affiliation(s)
- Letícia Pollo-Oliveira
- Faculdade de Ciências Farmacêuticas de Ribeirão Preto e Núcleo de Apoio à Pesquisa em Produtos Naturais e Sintéticos (NPPNS), Universidade de São Paulo, Av do Café , s/n, Ribeirão Preto, SP 14040-903, Brazil
| | - Harm Post
- Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences and Bijvoet Centre for Biomolecular Research, Utrecht University, Padualaan 8, Utrecht 3884 CH, The Netherlands
- Netherlands Proteomics Centre, Padualaan 8, Utrecht 3884 CH, The Netherlands
| | - Marcio Luis Acencio
- Botucatu Institute of Biosciences, UNESP - Univ Estadual Paulista, Distrito de Rubião Jr, s/n, Botucatu, São Paulo 18918-970, Brazil
| | - Ney Lemke
- Botucatu Institute of Biosciences, UNESP - Univ Estadual Paulista, Distrito de Rubião Jr, s/n, Botucatu, São Paulo 18918-970, Brazil
| | - Henk van den Toorn
- Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences and Bijvoet Centre for Biomolecular Research, Utrecht University, Padualaan 8, Utrecht 3884 CH, The Netherlands
- Netherlands Proteomics Centre, Padualaan 8, Utrecht 3884 CH, The Netherlands
| | - Vinicius Tragante
- Division of Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands
- Division of Biomedical Genetics, Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Albert JR Heck
- Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences and Bijvoet Centre for Biomolecular Research, Utrecht University, Padualaan 8, Utrecht 3884 CH, The Netherlands
- Netherlands Proteomics Centre, Padualaan 8, Utrecht 3884 CH, The Netherlands
| | - AF Maarten Altelaar
- Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences and Bijvoet Centre for Biomolecular Research, Utrecht University, Padualaan 8, Utrecht 3884 CH, The Netherlands
- Netherlands Proteomics Centre, Padualaan 8, Utrecht 3884 CH, The Netherlands
| | - Ana Patrícia Yatsuda
- Faculdade de Ciências Farmacêuticas de Ribeirão Preto e Núcleo de Apoio à Pesquisa em Produtos Naturais e Sintéticos (NPPNS), Universidade de São Paulo, Av do Café , s/n, Ribeirão Preto, SP 14040-903, Brazil
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1537
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Bunnik EM, Chung DWD, Hamilton M, Ponts N, Saraf A, Prudhomme J, Florens L, Le Roch KG. Polysome profiling reveals translational control of gene expression in the human malaria parasite Plasmodium falciparum. Genome Biol 2013; 14:R128. [PMID: 24267660 PMCID: PMC4053746 DOI: 10.1186/gb-2013-14-11-r128] [Citation(s) in RCA: 114] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2013] [Accepted: 11/22/2013] [Indexed: 12/02/2022] Open
Abstract
Background In eukaryotic organisms, gene expression is regulated at multiple levels during the processes of transcription and translation. The absence of a tight regulatory network for transcription in the human malaria parasite suggests that gene expression may largely be controlled at post-transcriptional and translational levels. Results In this study, we compare steady-state mRNA and polysome-associated mRNA levels of Plasmodium falciparum at different time points during its asexual cell cycle. For more than 30% of its genes, we observe a delay in peak transcript abundance in the polysomal fraction as compared to the steady-state mRNA fraction, suggestive of strong translational control. Our data show that key regulatory mechanisms could include inhibitory activity of upstream open reading frames and translational repression of the major virulence gene family by intronic transcripts. In addition, we observe polysomal mRNA-specific alternative splicing events and widespread transcription of non-coding transcripts. Conclusions These different layers of translational regulation are likely to contribute to a complex network that controls gene expression in this eukaryotic pathogen. Disrupting the mechanisms involved in such translational control could provide novel anti-malarial strategies.
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1538
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Faulconbridge A, Burdett T, Brandizi M, Gostev M, Pereira R, Vasant D, Sarkans U, Brazma A, Parkinson H. Updates to BioSamples database at European Bioinformatics Institute. Nucleic Acids Res 2013; 42:D50-2. [PMID: 24265224 PMCID: PMC3965081 DOI: 10.1093/nar/gkt1081] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
The BioSamples database at the EBI (http://www.ebi.ac.uk/biosamples) provides an integration point for BioSamples information between technology specific databases at the EBI, projects such as ENCODE and reference collections such as cell lines. The database delivers a unified query interface and API to query sample information across EBI's databases and provides links back to assay databases. Sample groups are used to manage related samples, e.g. those from an experimental submission, or a single reference collection. Infrastructural improvements include a new user interface with ontological and key word queries, a new query API, a new data submission API, complete RDF data download and a supporting SPARQL endpoint, accessioning at the point of submission to the European Nucleotide Archive and European Genotype Phenotype Archives and improved query response times.
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Affiliation(s)
- Adam Faulconbridge
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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1539
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Genome-wide mapping of transcriptional start sites defines an extensive leaderless transcriptome in Mycobacterium tuberculosis. Cell Rep 2013; 5:1121-31. [PMID: 24268774 PMCID: PMC3898074 DOI: 10.1016/j.celrep.2013.10.031] [Citation(s) in RCA: 240] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2013] [Revised: 10/04/2013] [Accepted: 10/18/2013] [Indexed: 12/11/2022] Open
Abstract
Deciphering physiological changes that mediate transition of Mycobacterium tuberculosis between replicating and nonreplicating states is essential to understanding how the pathogen can persist in an individual host for decades. We have combined RNA sequencing (RNA-seq) of 5′ triphosphate-enriched libraries with regular RNA-seq to characterize the architecture and expression of M. tuberculosis promoters. We identified over 4,000 transcriptional start sites (TSSs). Strikingly, for 26% of the genes with a primary TSS, the site of transcriptional initiation overlapped with the annotated start codon, generating leaderless transcripts lacking a 5′ UTR and, hence, the Shine-Dalgarno sequence commonly used to initiate ribosomal engagement in eubacteria. Genes encoding proteins with active growth functions were markedly depleted from the leaderless transcriptome, and there was a significant increase in the overall representation of leaderless mRNAs in a starvation model of growth arrest. The high percentage of leaderless genes may have particular importance in the physiology of nonreplicating M. tuberculosis. A resource for the identification of in vitro active promoters in M. tuberculosis A quarter of all genes in M. tuberculosis are expressed as leaderless mRNAs Leaderless mRNAs are differentially associated with toxin-antitoxin modules Abundance of leaderless mRNAs increases during starvation-induced growth arrest
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1540
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ProfileDB: a resource for proteomics and cross-omics biomarker discovery. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2013; 1844:960-6. [PMID: 24270047 DOI: 10.1016/j.bbapap.2013.11.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Revised: 10/18/2013] [Accepted: 11/13/2013] [Indexed: 01/09/2023]
Abstract
The increasing size and complexity of high-throughput datasets pose a growing challenge for researchers. Often very different (cross-omics) techniques with individual data analysis pipelines are employed making a unified biomarker discovery strategy and a direct comparison of different experiments difficult and time consuming. Here we present the comprehensive web-based application ProfileDB. The application is designed to integrate data from different high-throughput 'omics' data types (Transcriptomics, Proteomics, Metabolomics) with clinical parameters and prior knowledge on pathways and ontologies. Beyond data storage, ProfileDB provides a set of dedicated tools for study inspection and data visualization. The user can gain insights into a complex experiment with just a few mouse clicks. We will demonstrate the application by presenting typical use cases for the identification of proteomics biomarkers. All presented analyses can be reproduced using the public ProfileDB web server. The ProfileDB application is available by standard browser (Firefox 18+, Internet Explorer Version 9+) technology via http://profileDB.-microdiscovery.de/ (login and pass-word: profileDB). The installation contains several public datasets including different cross-'omics' experiments. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.
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1541
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Iwata K, Café-Mendes CC, Schmitt A, Steiner J, Manabe T, Matsuzaki H, Falkai P, Turck CW, Martins-de-Souza D. The human oligodendrocyte proteome. Proteomics 2013; 13:3548-53. [DOI: 10.1002/pmic.201300201] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2013] [Revised: 08/28/2013] [Accepted: 10/07/2013] [Indexed: 11/08/2022]
Affiliation(s)
- Keiko Iwata
- Department of Psychiatry and Psychotherapy; Ludwig Maximilians University of Munich (LMU); Munich Germany
- Research Center for Child Mental Development; University of Fukui; Japan
- Department of Development of Functional Brain Activities; United Graduate School of Child Development; Osaka University, Kanazawa University, Hamamatsu University School of Medicine; Chiba University and University of Fukui; Fukui Japan
| | - Cecilia C. Café-Mendes
- Max Planck Institute for Psychiatry; Proteomics and Biomarkers; Munich Germany
- Lab. de Neurobiologia Celular, Inst. Ciências Biomédicas; Universidade de São Paulo (USP); São Paulo SP Brazil
| | - Andrea Schmitt
- Department of Psychiatry and Psychotherapy; Ludwig Maximilians University of Munich (LMU); Munich Germany
- Lab. de Neurociências (LIM-27); Inst. de Psiquaitria, Faculdade de Medicina da Universidade de Sao Paulo; São Paulo Brazil
| | - Johann Steiner
- Department of Psychiatry; University of Magdeburg; Magdeburg Germany
| | - Takayuki Manabe
- Division of Gene Expression Mechanism; Institute for Comprehensive Medical Science; Fujita Health University; Aichi Japan
| | - Hideo Matsuzaki
- Research Center for Child Mental Development; University of Fukui; Japan
- Department of Development of Functional Brain Activities; United Graduate School of Child Development; Osaka University, Kanazawa University, Hamamatsu University School of Medicine; Chiba University and University of Fukui; Fukui Japan
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy; Ludwig Maximilians University of Munich (LMU); Munich Germany
| | - Christoph W. Turck
- Max Planck Institute for Psychiatry; Proteomics and Biomarkers; Munich Germany
| | - Daniel Martins-de-Souza
- Department of Psychiatry and Psychotherapy; Ludwig Maximilians University of Munich (LMU); Munich Germany
- Max Planck Institute for Psychiatry; Proteomics and Biomarkers; Munich Germany
- Lab. de Neurociências (LIM-27); Inst. de Psiquaitria, Faculdade de Medicina da Universidade de Sao Paulo; São Paulo Brazil
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1542
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Schmidt A, Trentini DB, Spiess S, Fuhrmann J, Ammerer G, Mechtler K, Clausen T. Quantitative phosphoproteomics reveals the role of protein arginine phosphorylation in the bacterial stress response. Mol Cell Proteomics 2013; 13:537-50. [PMID: 24263382 DOI: 10.1074/mcp.m113.032292] [Citation(s) in RCA: 96] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Arginine phosphorylation is an emerging protein modification implicated in the general stress response of Gram-positive bacteria. The modification is mediated by the arginine kinase McsB, which phosphorylates and inactivates the heat shock repressor CtsR. In this study, we developed a mass spectrometric approach accounting for the peculiar chemical properties of phosphoarginine. The improved methodology was used to analyze the dynamic changes in the Bacillus subtilis arginine phosphoproteome in response to different stress situations. Quantitative analysis showed that a B. subtilis mutant lacking the YwlE arginine phosphatase accumulated a strikingly large number of arginine phosphorylations (217 sites in 134 proteins), however only a minor fraction of these sites was increasingly modified during heat shock or oxidative stress. The main targets of McsB-mediated arginine phosphorylation comprise central factors of the stress response system including the CtsR and HrcA heat shock repressors, as well as major components of the protein quality control system such as the ClpCP protease and the GroEL chaperonine. These findings highlight the impact of arginine phosphorylation in orchestrating the bacterial stress response.
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Affiliation(s)
- Andreas Schmidt
- Research Institute of Molecular Pathology - IMP, Dr. Bohr-Gasse 7, A-1030 Vienna, Austria
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1543
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Metastatic castration-resistant prostate cancer reveals intrapatient similarity and interpatient heterogeneity of therapeutic kinase targets. Proc Natl Acad Sci U S A 2013; 110:E4762-9. [PMID: 24248375 DOI: 10.1073/pnas.1319948110] [Citation(s) in RCA: 95] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
In prostate cancer, multiple metastases from the same patient share similar copy number, mutational status, erythroblast transformation specific (ETS) rearrangements, and methylation patterns supporting their clonal origins. Whether actionable targets such as tyrosine kinases are also similarly expressed and activated in anatomically distinct metastatic lesions of the same patient is not known. We evaluated active kinases using phosphotyrosine peptide enrichment and quantitative mass spectrometry to identify druggable targets in metastatic castration-resistant prostate cancer obtained at rapid autopsy. We identified distinct phosphopeptide patterns in metastatic tissues compared with treatment-naive primary prostate tissue and prostate cancer cell line-derived xenografts. Evaluation of metastatic castration-resistant prostate cancer samples for tyrosine phosphorylation and upstream kinase targets revealed SRC, epidermal growth factor receptor (EGFR), rearranged during transfection (RET), anaplastic lymphoma kinase (ALK), and MAPK1/3 and other activities while exhibiting intrapatient similarity and interpatient heterogeneity. Phosphoproteomic analyses and identification of kinase activation states in metastatic castration-resistant prostate cancer patients have allowed for the prioritization of kinases for further clinical evaluation.
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1544
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Wattam AR, Abraham D, Dalay O, Disz TL, Driscoll T, Gabbard JL, Gillespie JJ, Gough R, Hix D, Kenyon R, Machi D, Mao C, Nordberg EK, Olson R, Overbeek R, Pusch GD, Shukla M, Schulman J, Stevens RL, Sullivan DE, Vonstein V, Warren A, Will R, Wilson MJC, Yoo HS, Zhang C, Zhang Y, Sobral BW. PATRIC, the bacterial bioinformatics database and analysis resource. Nucleic Acids Res 2013; 42:D581-91. [PMID: 24225323 PMCID: PMC3965095 DOI: 10.1093/nar/gkt1099] [Citation(s) in RCA: 916] [Impact Index Per Article: 76.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10,000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.
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Affiliation(s)
- Alice R Wattam
- Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24060, USA, Computation Institute, University of Chicago, Chicago, IL 60637, USA, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60637, USA, Grado Department of Industrial & Systems Engineering, Virginia Tech, Blacksburg, VA 24060, USA, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Fellowship for Interpretation of Genomes, Burr Ridge, IL 60527, USA, Computing, Environment, and Life Sciences, Argonne National Laboratory, Argonne, IL 60637, USA and Nestlé Institute of Health Sciences SA, Campus EPFL, Quartier de L'innovation, Lausanne, Switzerland
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1545
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Identification of telomere-associated molecules by engineered DNA-binding molecule-mediated chromatin immunoprecipitation (enChIP). Sci Rep 2013; 3:3171. [PMID: 24201379 PMCID: PMC3821016 DOI: 10.1038/srep03171] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2013] [Accepted: 10/24/2013] [Indexed: 11/09/2022] Open
Abstract
Biochemical analysis of molecular interactions in specific genomic regions requires their isolation while retaining molecular interactions in vivo. Here, we report isolation of telomeres by engineered DNA-binding molecule-mediated chromatin immunoprecipitation (enChIP) using a transcription activator-like (TAL) protein recognizing telomere repeats. Telomeres recognized by the tagged TAL protein were immunoprecipitated with an antibody against the tag and subjected to identification of telomere-binding molecules. enChIP-mass spectrometry (enChIP-MS) targeting telomeres identified known and novel telomere-binding proteins. The data have been deposited to the ProteomeXchange with identifier PXD000461. In addition, we showed that RNA associated with telomeres could be isolated by enChIP. Identified telomere-binding molecules may play important roles in telomere biology. enChIP using TAL proteins would be a useful tool for biochemical analysis of specific genomic regions of interest.
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1546
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Staes A, Vandenbussche J, Demol H, Goethals M, Yilmaz Ş, Hulstaert N, Degroeve S, Kelchtermans P, Martens L, Gevaert K. Asn3, a reliable, robust, and universal lock mass for improved accuracy in LC-MS and LC-MS/MS. Anal Chem 2013; 85:11054-60. [PMID: 24134513 DOI: 10.1021/ac4027093] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The use of internal calibrants (the so-called lock mass approach) provides much greater accuracy in mass spectrometry based proteomics. However, the polydimethylcyclosiloxane (PCM) peaks commonly used for this purpose are quite unreliable, leading to missing calibrant peaks in spectra and correspondingly lower mass measurement accuracy. Therefore, we here introduce a universally applicable and robust internal calibrant, the tripeptide Asn3. We show that Asn3 is a substantial improvement over PCM both in terms of consistent detection and resulting mass measurement accuracy. Asn3 is also very easy to adopt in the lab, as it requires only minor adjustments to the analytical setup.
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Affiliation(s)
- An Staes
- Department of Medical Protein Research, VIB , B-9000 Ghent, Belgium
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1547
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Cappellini E, Gentry A, Palkopoulou E, Ishida Y, Cram D, Roos AM, Watson M, Johansson US, Fernholm B, Agnelli P, Barbagli F, Littlewood DTJ, Kelstrup CD, Olsen JV, Lister AM, Roca AL, Dalén L, Gilbert MTP. Resolution of the type material of the Asian elephant,Elephas maximusLinnaeus, 1758 (Proboscidea, Elephantidae). Zool J Linn Soc 2013. [DOI: 10.1111/zoj.12084] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Affiliation(s)
- Enrico Cappellini
- Centre for GeoGenetics; Natural History Museum of Denmark; University of Copenhagen; Øster Voldgade 5-7 1350 Copenhagen Denmark
| | - Anthea Gentry
- Natural History Museum; Cromwell Road London SW7 5BD UK
| | - Eleftheria Palkopoulou
- Department of Bioinformatics and Genetics; Swedish Museum of Natural History; SE-10405 Stockholm Sweden
- Department of Zoology; Stockholm University; SE-10691 Stockholm Sweden
| | - Yasuko Ishida
- Department of Animal Sciences; University of Illinois at Urbana-Champaign; Urbana Illinois 61801 USA
| | - David Cram
- Jesus College; Turl Street Oxford OX1 3DW UK
| | - Anna-Marie Roos
- Lincoln School of Humanities; University of Lincoln; Brayford Pool Lincoln LN6 7TS UK
| | - Mick Watson
- The Roslin Institute; University of Edinburgh; Midlothian EH25 9RG UK
| | - Ulf S. Johansson
- Department of Zoology; Swedish Museum of Natural History; SE-10405 Stockholm Sweden
| | - Bo Fernholm
- Department of Zoology; Swedish Museum of Natural History; SE-10405 Stockholm Sweden
| | - Paolo Agnelli
- Natural History Museum of Florence; via Romana 17 50125 Florence Italy
| | - Fausto Barbagli
- Natural History Museum of Florence; via Romana 17 50125 Florence Italy
| | | | - Christian D. Kelstrup
- Novo Nordisk Foundation Center for Protein Research; Faculty of Health Sciences; University of Copenhagen; Blegdamsvej 3b 2200 Copenhagen Denmark
| | - Jesper V. Olsen
- Novo Nordisk Foundation Center for Protein Research; Faculty of Health Sciences; University of Copenhagen; Blegdamsvej 3b 2200 Copenhagen Denmark
| | | | - Alfred L. Roca
- Department of Animal Sciences; University of Illinois at Urbana-Champaign; Urbana Illinois 61801 USA
| | - Love Dalén
- Department of Bioinformatics and Genetics; Swedish Museum of Natural History; SE-10405 Stockholm Sweden
| | - M. Thomas P. Gilbert
- Centre for GeoGenetics; Natural History Museum of Denmark; University of Copenhagen; Øster Voldgade 5-7 1350 Copenhagen Denmark
- Ancient DNA Laboratory; Murdoch University; South St Perth Western Australia 6150 Australia
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1548
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de Poot SAH, Lai KW, van der Wal L, Plasman K, Van Damme P, Porter AC, Gevaert K, Bovenschen N. Granzyme M targets topoisomerase II alpha to trigger cell cycle arrest and caspase-dependent apoptosis. Cell Death Differ 2013; 21:416-26. [PMID: 24185622 DOI: 10.1038/cdd.2013.155] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2013] [Revised: 09/23/2013] [Accepted: 09/26/2013] [Indexed: 12/31/2022] Open
Abstract
Cytotoxic lymphocyte protease granzyme M (GrM) is a potent inducer of tumor cell death. The apoptotic phenotype and mechanism by which it induces cell death, however, remain poorly understood and controversial. Here, we show that GrM-induced cell death was largely caspase-dependent with various hallmarks of classical apoptosis, coinciding with caspase-independent G2/M cell cycle arrest. Using positional proteomics in human tumor cells, we identified the nuclear enzyme topoisomerase II alpha (topoIIα) as a physiological substrate of GrM. Cleavage of topoIIα by GrM at Leu(1280) separated topoIIα functional domains from the nuclear localization signals, leading to nuclear exit of topoIIα catalytic activity, thereby rendering it nonfunctional. Similar to the apoptotic phenotype of GrM, topoIIα depletion in tumor cells led to cell cycle arrest in G2/M, mitochondrial perturbations, caspase activation, and apoptosis. We conclude that cytotoxic lymphocyte protease GrM targets topoIIα to trigger cell cycle arrest and caspase-dependent apoptosis.
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Affiliation(s)
- S A H de Poot
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - K W Lai
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - L van der Wal
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - K Plasman
- 1] Department of Medical Protein Research,VIB, Ghent, B-9000, Belgium [2] Department of Biochemistry, Ghent University, Ghent B-9000, Belgium
| | - P Van Damme
- 1] Department of Medical Protein Research,VIB, Ghent, B-9000, Belgium [2] Department of Biochemistry, Ghent University, Ghent B-9000, Belgium
| | - A C Porter
- Centre for Haematology, Faculty of Medicine, Imperial College London, London, UK
| | - K Gevaert
- 1] Department of Medical Protein Research,VIB, Ghent, B-9000, Belgium [2] Department of Biochemistry, Ghent University, Ghent B-9000, Belgium
| | - N Bovenschen
- 1] Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands [2] Laboratory for Translational Immunology, University Medical Center Utrecht, Utrecht, The Netherlands
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1549
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Nanjo Y, Nakamura T, Komatsu S. Identification of indicator proteins associated with flooding injury in soybean seedlings using label-free quantitative proteomics. J Proteome Res 2013; 12:4785-98. [PMID: 23659366 DOI: 10.1021/pr4002349] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Flooding injury is one of the abiotic constraints on soybean growth. An experimental system established for evaluating flooding injury in soybean seedlings indicated that the degree of injury is dependent on seedling density in floodwater. Dissolved oxygen levels in the floodwater were decreased by the seedlings and correlated with the degree of injury. To understand the molecular mechanism responsible for the injury, proteomic alterations in soybean seedlings that correlated with severity of stress were analyzed using label-free quantitative proteomics. The analysis showed that the abundance of proteins involved in cell wall modification, such as polygalacturonase inhibitor-like and expansin-like B1-like proteins, which may be associated with the defense system, increased dependence on stress at both the protein and mRNA levels in all organs during flooding. The manner of alteration in abundance of these proteins was distinct from those of other responsive proteins. Furthermore, proteins also showing specific changes in abundance in the root tip included protein phosphatase 2A subunit-like proteins, which are possibly involved in flooding-induced root tip cell death. Additionally, decreases in abundance of cell wall synthesis-related proteins, such as cinnamyl-alcohol dehydrogenase and cellulose synthase-interactive protein-like proteins, were identified in hypocotyls of seedlings grown for 3 days after flooding, and these proteins may be associated with suppression of growth after flooding. These flooding injury-associated proteins can be defined as indicator proteins for severity of flooding stress in soybean.
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Affiliation(s)
- Yohei Nanjo
- NARO Institute of Crop Science , Tsukuba 305-8518, Japan
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1550
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Salek M, McGowan S, Trudgian DC, Dushek O, de Wet B, Efstathiou G, Acuto O. Quantitative phosphoproteome analysis unveils LAT as a modulator of CD3ζ and ZAP-70 tyrosine phosphorylation. PLoS One 2013; 8:e77423. [PMID: 24204825 PMCID: PMC3813684 DOI: 10.1371/journal.pone.0077423] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2013] [Accepted: 09/10/2013] [Indexed: 11/25/2022] Open
Abstract
Signaling through the T cell receptor (TCR) initiates adaptive immunity and its perturbation may results in autoimmunity. The plasma membrane scaffolding protein LAT acts as a central organizer of the TCR signaling machinery to activate many functional pathways. LAT-deficient mice develop an autoimmune syndrome but the mechanism of this pathology is unknown. In this work we have compared global dynamics of TCR signaling by MS-based quantitative phosphoproteomics in LAT-sufficient and LAT-defective Jurkat T cells. Surprisingly, we found that many TCR-induced phosphorylation events persist in the absence of LAT, despite ERK and PLCγ1 phosphorylation being repressed. Most importantly, the absence of LAT resulted in augmented and persistent tyrosine phosphorylation of CD3ζ and ZAP70. This indicates that LAT signaling hub is also implicated in negative feedback signals to modulate upstream phosphorylation events. Phosphorylation kinetics data resulting from this investigation is documented in a database (phosphoTCR) accessible online. The MS data have been deposited to the ProteomeXchange with identifier PXD000341.
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Affiliation(s)
- Mogjiborahman Salek
- T cell Signaling Laboratory, Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
- * E-mail: (OA); (MS)
| | - Simon McGowan
- Computational Biology Research Group, Nuffield Department of Medicine, University of Oxford, Headington, Oxford, United Kingdom
| | - David C. Trudgian
- Central Proteomics Facility, Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Omer Dushek
- Molecular Immunology Group, Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Ben de Wet
- T cell Signaling Laboratory, Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
- Central Proteomics Facility, Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Georgios Efstathiou
- T cell Signaling Laboratory, Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Oreste Acuto
- T cell Signaling Laboratory, Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
- * E-mail: (OA); (MS)
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