301
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302
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Mehnert M, Li W, Wu C, Salovska B, Liu Y. Combining Rapid Data Independent Acquisition and CRISPR Gene Deletion for Studying Potential Protein Functions: A Case of HMGN1. Proteomics 2019; 19:e1800438. [PMID: 30901150 DOI: 10.1002/pmic.201800438] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 02/24/2019] [Indexed: 12/21/2022]
Abstract
CRISPR-Cas gene editing holds substantial promise in many biomedical disciplines and basic research. Due to the important functional implications of non-histone chromosomal protein HMG-14 (HMGN1) in regulating chromatin structure and tumor immunity, gene knockout of HMGN1 is performed by CRISPR in cancer cells and the following proteomic regulation events are studied. In particular, DIA mass spectrometry (DIA-MS) is utilized, and more than 6200 proteins (protein- FDR 1%) and more than 82 000 peptide precursors are reproducibly measured in the single MS shots of 2 h. HMGN1 protein deletion is confidently verified by DIA-MS in all of the clone- and dish- replicates following CRISPR. Statistical analysis reveals 147 proteins change their expressions significantly after HMGN1 knockout. Functional annotation and enrichment analysis indicate the deletion of HMGN1 induces histone inactivation, various stress pathways, remodeling of extracellular proteomes, cell proliferation, as well as immune regulation processes such as complement and coagulation cascade and interferon alpha/ gamma response in cancer cells. These results shed new lights on the cellular functions of HMGN1. It is suggested that DIA-MS can be reliably used as a rapid, robust, and cost-effective proteomic-screening tool to assess the outcome of the CRISPR experiments.
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Affiliation(s)
- Martin Mehnert
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, 8093, Switzerland
| | - Wenxue Li
- Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA
| | - Chongde Wu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA
| | - Barbora Salovska
- Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA.,Department of Genome Integrity, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, 14220, Czech Republic
| | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, 06516, USA.,Department of Pharmacology, Yale University School of Medicine, New Haven, CT, 06520, USA
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303
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Sun Z, Chang HM, Wang A, Song J, Zhang X, Guo J, Leung PCK, Lian F. Identification of potential metabolic biomarkers of polycystic ovary syndrome in follicular fluid by SWATH mass spectrometry. Reprod Biol Endocrinol 2019; 17:45. [PMID: 31186025 PMCID: PMC6560878 DOI: 10.1186/s12958-019-0490-y] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 06/04/2019] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Polycystic ovary syndrome (PCOS) is a complex disorder associated with multiple metabolic disturbance, including defective glucose metabolism and insulin resistance. The altered metabolites caused by the related metabolic disturbance may affect ovarian follicles, which can be reflected in follicular fluid composition. The aim of this study is to investigate follicular fluid metabolic profiles in women with PCOS using an advanced sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry. MATERIALS AND METHODS Nineteen women with PCOS and twenty-one healthy controls undergoing IVF/ET were recruited, and their follicular fluid samples were collected for metabolomic study. Follicular fluid metabolic profiles, including steroid hormones, free fatty acids, bioactive lipids, and amino acids were analyzed using the principal component analysis (PCA) and partial least squares to latent structure-discriminant analysis (PLS-DA) model. RESULTS Levels of free fatty acids, 3-hydroxynonanoyl carnitine and eicosapentaenoic acid were significantly increased (P < 0.05), whereas those of bioactive lipids, lysophosphatidylcholines (LysoPC) (16:0), phytosphingosine, LysoPC (14:0) and LysoPC (18:0) were significantly decreased in women with PCOS (P < 0.05). Additionally, levels of steroid hormone deoxycorticosterone and two amino acids, phenylalanine and leucine were higher in the PCOS patients (P < 0.05). CONCLUSION Women with PCOS display unique metabolic profiles in their follicular fluid, and this data may provide us with important biochemical information and metabolic signatures that enable a better understanding of the pathogenesis of PCOS.
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Affiliation(s)
- Zhengao Sun
- grid.479672.9Integrative Medicine Research Centre of Reproduction and Heredity, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No 42 Wen Hua Xi Road, Jinan, 250011 China
- 0000 0001 2288 9830grid.17091.3eDepartment of Obstetrics and Gynaecology, BC Children’s Hospital Research Institute, University of British Columbia, Vancouver, British Columbia V6H 3V5 Canada
| | - Hsun-Ming Chang
- grid.479672.9Integrative Medicine Research Centre of Reproduction and Heredity, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No 42 Wen Hua Xi Road, Jinan, 250011 China
- 0000 0001 2288 9830grid.17091.3eDepartment of Obstetrics and Gynaecology, BC Children’s Hospital Research Institute, University of British Columbia, Vancouver, British Columbia V6H 3V5 Canada
| | - Aijuan Wang
- grid.479672.9Integrative Medicine Research Centre of Reproduction and Heredity, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No 42 Wen Hua Xi Road, Jinan, 250011 China
| | - Jingyan Song
- grid.479672.9Integrative Medicine Research Centre of Reproduction and Heredity, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No 42 Wen Hua Xi Road, Jinan, 250011 China
| | - Xingxing Zhang
- grid.479672.9Integrative Medicine Research Centre of Reproduction and Heredity, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No 42 Wen Hua Xi Road, Jinan, 250011 China
| | - Jiayin Guo
- 0000 0000 8877 7471grid.284723.8Guandong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515 China
| | - Peter C. K. Leung
- grid.479672.9Integrative Medicine Research Centre of Reproduction and Heredity, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No 42 Wen Hua Xi Road, Jinan, 250011 China
- 0000 0001 2288 9830grid.17091.3eDepartment of Obstetrics and Gynaecology, BC Children’s Hospital Research Institute, University of British Columbia, Vancouver, British Columbia V6H 3V5 Canada
- 0000 0001 2288 9830grid.17091.3eDepartment of Obstetrics and Gynaecology, BC Children’s Hospital Research Institute, University of British Columbia, Room 317, 950 West 28th Avenue, Vancouver, British Columbia V5Z 4H4 Canada
| | - Fang Lian
- grid.479672.9Integrative Medicine Research Centre of Reproduction and Heredity, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No 42 Wen Hua Xi Road, Jinan, 250011 China
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304
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Kadokami K, Ueno D. Comprehensive Target Analysis for 484 Organic Micropollutants in Environmental Waters by the Combination of Tandem Solid-Phase Extraction and Quadrupole Time-of-Flight Mass Spectrometry with Sequential Window Acquisition of All Theoretical Fragment-Ion Spectra Acquisition. Anal Chem 2019; 91:7749-7755. [PMID: 31132244 DOI: 10.1021/acs.analchem.9b01141] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
There are many thousands of chemicals in use for a wide range of purposes, and highly efficient analytical methods are required to monitor them for protection of the environment. In order to cope with this difficult task we developed a novel, comprehensive method for 484 substances in water samples. In this method target chemicals were extracted by tandem SPE and then determined by LC-QTOF-MS-SWATH. Targets were unambiguously identified using retention times, accurate masses of a precursor and two product ions, their ion ratios, and accurate MS/MS spectrum. Quantitation was achieved by the internal standard method using a precursor ion. Results of recovery tests at two concentrations (50 and 500 ng L-1) showed average recoveries of 87.5% and 87.0% (RSD, 9.1% and 9.4%), respectively. Limits of detection of one-half of the targets were below 1.0 ng L-1. The method was applied to the influent and effluent of a sewage treatment plant, and around 100 chemicals were detected. Results of examination on matrix effects using their extracts spiked with 209 pesticides showed that the ratios of detected amounts between the extracts and the standard solution were 89.8% (influent) and 91.7% (effluent), respectively. In addition, investigation on the stability of calibration curves by injecting the same standards for 1 year showed that their quantitative results did not change; average accuracy was 103.3% (RSD, 10.0%), indicating that the calibration curves can be used for an extended period of time without calibration, and quantitative retrospective analysis can be done after creating calibration curves for new targets.
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Affiliation(s)
- Kiwao Kadokami
- Institute of Environmental Science and Technology , The University of Kitakyushu , 1-1 Hibikino, Wakamatsu , Kitakyushu , Japan
| | - Daisuke Ueno
- Graduate School of Agriculture , Saga University , 1 Honjyo, Honjyo-machi , Saga , Japan
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305
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Comparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins. Nat Commun 2019; 10:2524. [PMID: 31175306 PMCID: PMC6555818 DOI: 10.1038/s41467-019-10513-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Accepted: 05/16/2019] [Indexed: 01/18/2023] Open
Abstract
Deterioration of biomolecules in clinical tissues is an inevitable pre-analytical process, which affects molecular measurements and thus potentially confounds conclusions from cohort analyses. Here, we investigate the degradation of mRNA and protein in 68 pairs of adjacent prostate tissue samples using RNA-Seq and SWATH mass spectrometry, respectively. To objectively quantify the extent of protein degradation, we develop a numerical score, the Proteome Integrity Number (PIN), that faithfully measures the degree of protein degradation. Our results indicate that protein degradation only affects 5.9% of the samples tested and shows negligible correlation with mRNA degradation in the adjacent samples. These findings are confirmed by independent analyses on additional clinical sample cohorts and across different mass spectrometric methods. Overall, the data show that the majority of samples tested are not compromised by protein degradation, and establish the PIN score as a generic and accurate indicator of sample quality for proteomic analyses. Protein degradation in clinical samples is largely unexplored. Here, the authors analyze the transcriptome and proteome of clinical tissue samples and develop an algorithm to assess protein degradation, showing that protein degradation is negligible in most tissue samples and does not correlate with transcript degradation.
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306
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He Y, Mohamedali A, Huang C, Baker MS, Nice EC. Oncoproteomics: Current status and future opportunities. Clin Chim Acta 2019; 495:611-624. [PMID: 31176645 DOI: 10.1016/j.cca.2019.06.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 06/05/2019] [Accepted: 06/05/2019] [Indexed: 02/07/2023]
Abstract
Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.
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Affiliation(s)
- Yujia He
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, PR China
| | - Abidali Mohamedali
- Department of Molecular Sciences, Faculty of Science and Engineering, Macquarie University, New South Wales 2109, Australia
| | - Canhua Huang
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, PR China
| | - Mark S Baker
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, New South Wales 2109, Australia.
| | - Edouard C Nice
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, PR China; Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, New South Wales 2109, Australia; Department of Biochemistry and Molecular Biology, Monash University, Clayton, Australia.
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307
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Iacobucci C, Piotrowski C, Aebersold R, Amaral BC, Andrews P, Bernfur K, Borchers C, Brodie NI, Bruce JE, Cao Y, Chaignepain S, Chavez JD, Claverol S, Cox J, Davis T, Degliesposti G, Dong MQ, Edinger N, Emanuelsson C, Gay M, Götze M, Gomes-Neto F, Gozzo FC, Gutierrez C, Haupt C, Heck AJR, Herzog F, Huang L, Hoopmann MR, Kalisman N, Klykov O, Kukačka Z, Liu F, MacCoss MJ, Mechtler K, Mesika R, Moritz RL, Nagaraj N, Nesati V, Neves-Ferreira AGC, Ninnis R, Novák P, O’Reilly FJ, Pelzing M, Petrotchenko E, Piersimoni L, Plasencia M, Pukala T, Rand KD, Rappsilber J, Reichmann D, Sailer C, Sarnowski CP, Scheltema RA, Schmidt C, Schriemer DC, Shi Y, Skehel JM, Slavin M, Sobott F, Solis-Mezarino V, Stephanowitz H, Stengel F, Stieger CE, Trabjerg E, Trnka M, Vilaseca M, Viner R, Xiang Y, Yilmaz S, Zelter A, Ziemianowicz D, Leitner A, Sinz A. First Community-Wide, Comparative Cross-Linking Mass Spectrometry Study. Anal Chem 2019; 91:6953-6961. [PMID: 31045356 PMCID: PMC6625963 DOI: 10.1021/acs.analchem.9b00658] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats. Such consensus formats should become accepted in the field and be shown to lead to reproducible results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. Our study therefore builds the framework for establishing best practice guidelines to conduct cross-linking experiments, perform data analysis, and define reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.
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Affiliation(s)
- Claudio Iacobucci
- Department of Pharmaceutical Chemistry and Bioanalytics, Institute
of Pharmacy, Charles Tanford Protein Center, Martin Luther University
Halle-Wittenberg, Kurt-Mothes-Strasse 3a, 06120 Halle/Saale, Germany
| | - Christine Piotrowski
- Department of Pharmaceutical Chemistry and Bioanalytics, Institute
of Pharmacy, Charles Tanford Protein Center, Martin Luther University
Halle-Wittenberg, Kurt-Mothes-Strasse 3a, 06120 Halle/Saale, Germany
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH
Zurich, Otto-Stern-Weg 3, 8093 Zurich, Switzerland
- Faculty of Science, University of Zurich, 8006 Zurich,
Switzerland
| | - Bruno C. Amaral
- Institute of Chemistry, University of Campinas, Campinas São
Paulo 13083-970, Brazil
| | - Philip Andrews
- Departments of Biological Chemistry, Bioinformatics, and Chemistry,
University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Katja Bernfur
- Department of Biochemistry and Structural Biology, Center for
Molecular Protein Science, Lund University, 221 00 Lund, Sweden
| | - Christoph Borchers
- University of Victoria–Genome British Columbia Proteomics
Centre, Vancouver Island Technology Park, Victoria, British Columbia V8Z 7X8,
Canada
- Department of Biochemistry and Microbiology, University of Victoria,
Petch Building, Room 270d, 3800 Finnerty Road, Victoria, British Columbia V8P 5C2,
Canada
- Gerald Bronfman Department of Oncology, Jewish General Hospital,
McGill University, 3755 Côte Ste-Catherine Road, Montréal, Quebec H3T
1E2, Canada
- Proteomics Centre, Segal Cancer Centre, Lady Davis Institute, Jewish
General Hospital, McGill University, 3755 Côte Ste-Catherine Road,
Montréal, Quebec H3T 1E2, Canada
| | - Nicolas I. Brodie
- University of Victoria–Genome British Columbia Proteomics
Centre, Vancouver Island Technology Park, Victoria, British Columbia V8Z 7X8,
Canada
| | - James E. Bruce
- Department of Genome Sciences, University of Washington, Seattle,
Washington 98195, United States
| | - Yong Cao
- National Institute of Biological Sciences, Beijing 7 Science Park
Road, ZGC Life Science Park, 102206 Beijing, China
| | - Stéphane Chaignepain
- CBMN, UMR 5248, CNRS, Université de Bordeaux, INP Bordeaux,
Pessac 33607, France
| | - Juan D. Chavez
- Department of Genome Sciences, University of Washington, Seattle,
Washington 98195, United States
| | - Stéphane Claverol
- Centre de Génomique Fonctionnelle, Plateforme
Protéome, Université de Bordeaux, Bordeaux33000, France
| | - Jürgen Cox
- Computational Systems Biochemistry Research Group,
Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried,
Germany
| | - Trisha Davis
- Department of Biochemistry, University of Washington, Seattle,
Washington 98195, United States
| | - Gianluca Degliesposti
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus,
Francis Crick Avenue, Cambridge CB2 0QH, U.K
| | - Meng-Qiu Dong
- National Institute of Biological Sciences, Beijing 7 Science Park
Road, ZGC Life Science Park, 102206 Beijing, China
| | - Nufar Edinger
- Department of Biological Chemistry, The Alexander Silberman
Institute of Life Sciences, Safra Campus Givat Ram, The Hebrew University of
Jerusalem, Jerusalem 91904, Israel
| | - Cecilia Emanuelsson
- Department of Biochemistry and Structural Biology, Center for
Molecular Protein Science, Lund University, 221 00 Lund, Sweden
| | - Marina Gay
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona
Institute of Science and Technology (BIST), Baldiri Reixac 10, 08028 Barcelona,
Spain
| | - Michael Götze
- Institute for Biochemistry and Biotechnology, Charles Tanford
Protein Center, Martin Luther University Halle-Wittenberg, Kurt-Mothes-Strasse 3a,
06120 Halle/Saale, Germany
| | - Francisco Gomes-Neto
- Laboratory of Toxinology, Oswaldo Cruz Institute, Fiocruz, Avenida
Brasil 4365 (Moorish Castle), Manguinhos, Rio de Janeiro, Rio de Janeiro 21040-900,
Brazil
| | - Fabio C. Gozzo
- Institute of Chemistry, University of Campinas, Campinas São
Paulo 13083-970, Brazil
| | - Craig Gutierrez
- Department of Physiology & Biophysics, University of
California, Irvine, California 92697, United States
| | - Caroline Haupt
- Interdisciplinary Research Center HALOmem, Institute for
Biochemistry and Biotechnology, Charles Tanford Protein Center, Martin Luther
University Halle-Wittenberg, Kurt-Mothes-Strasse 3a, 06120 Halle/Saale,
Germany
| | - Albert J. R. Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for
Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University
of Utrecht and Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, The
Netherlands
| | - Franz Herzog
- Gene Center Munich, Department of Biochemistry, Faculty of Chemistry
and Pharmacy, Ludwig Maximilians University of Munich, Feodor-Lynen-Strasse 25,
81377 Munich, Germany
| | - Lan Huang
- Department of Physiology & Biophysics, University of
California, Irvine, California 92697, United States
| | - Michael R. Hoopmann
- Institute for Systems Biology, 401 Terry Avenue North, Seattle,
Washington 98109, United States
| | - Nir Kalisman
- Department of Biological Chemistry, The Alexander Silberman
Institute of Life Sciences, Safra Campus Givat Ram, The Hebrew University of
Jerusalem, Jerusalem 91904, Israel
| | - Oleg Klykov
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for
Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University
of Utrecht and Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, The
Netherlands
| | - Zdeněk Kukačka
- Institute of Microbiology, BIOCEV, Prumyslova 595, 252 50 Vestec,
Czech Republic
| | - Fan Liu
- Leibniz Institute of Molecular Pharmacology (FMP),
Robert-Rössle-Strasse 10, 13125 Berlin, Germany
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle,
Washington 98195, United States
| | - Karl Mechtler
- Protein Chemistry Facility, Research Institute of Molecular
Pathology (IMP) and Institute of Molecular Biotechnology (IMBA), Vienna Biocenter
(VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Ravit Mesika
- Department of Biological Chemistry, The Alexander Silberman
Institute of Life Sciences, Safra Campus Givat Ram, The Hebrew University of
Jerusalem, Jerusalem 91904, Israel
| | - Robert L. Moritz
- Institute for Systems Biology, 401 Terry Avenue North, Seattle,
Washington 98109, United States
| | - Nagarjuna Nagaraj
- Biochemistry Core Facility, Max-Planck-Institute of Biochemistry,
Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Victor Nesati
- Analytical Biochemistry, CSL Limited, Bio21 Institute, 30
Flemington Road, 3010 Parkville, Melbourne, Australia
| | - Ana G. C. Neves-Ferreira
- Laboratory of Toxinology, Oswaldo Cruz Institute, Fiocruz, Avenida
Brasil 4365 (Moorish Castle), Manguinhos, Rio de Janeiro, Rio de Janeiro 21040-900,
Brazil
| | - Robert Ninnis
- Analytical Biochemistry, CSL Limited, Bio21 Institute, 30
Flemington Road, 3010 Parkville, Melbourne, Australia
| | - Petr Novák
- Institute of Microbiology, BIOCEV, Prumyslova 595, 252 50 Vestec,
Czech Republic
| | - Francis J. O’Reilly
- Chair of Bioanalytics, Institute of Biotechnology Technische
Universität Berlin, 13355 Berlin, Germany
| | - Matthias Pelzing
- Analytical Biochemistry, CSL Limited, Bio21 Institute, 30
Flemington Road, 3010 Parkville, Melbourne, Australia
| | - Evgeniy Petrotchenko
- University of Victoria–Genome British Columbia Proteomics
Centre, Vancouver Island Technology Park, Victoria, British Columbia V8Z 7X8,
Canada
| | - Lolita Piersimoni
- Departments of Biological Chemistry, Bioinformatics, and Chemistry,
University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Manolo Plasencia
- Departments of Biological Chemistry, Bioinformatics, and Chemistry,
University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Tara Pukala
- Discipline of Chemistry, Faculty of Sciences, University of
Adelaide, North Terrace, Adelaide, South Australia 5005, Australia
| | - Kasper D. Rand
- Department of Pharmacy, University of Copenhagen, 2100 Copenhagen,
Denmark
| | - Juri Rappsilber
- Chair of Bioanalytics, Institute of Biotechnology Technische
Universität Berlin, 13355 Berlin, Germany
- Wellcome Trust Centre for Cell Biology, School of Biological
Sciences, University of Edinburgh, EH9 3BF Edinburgh, U.K
| | - Dana Reichmann
- Department of Biological Chemistry, The Alexander Silberman
Institute of Life Sciences, Safra Campus Givat Ram, The Hebrew University of
Jerusalem, Jerusalem 91904, Israel
| | - Carolin Sailer
- University of Konstanz, Department of Biology,
Universitätsstrasse 10, 78457 Konstanz, Germany
| | - Chris P. Sarnowski
- Department of Biology, Institute of Molecular Systems Biology, ETH
Zurich, Otto-Stern-Weg 3, 8093 Zurich, Switzerland
- PhD Program in Systems Biology, University of Zurich and ETH
Zurich, 8092 Zurich, Switzerland
| | - Richard A. Scheltema
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for
Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University
of Utrecht and Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, The
Netherlands
| | - Carla Schmidt
- Interdisciplinary Research Center HALOmem, Institute for
Biochemistry and Biotechnology, Charles Tanford Protein Center, Martin Luther
University Halle-Wittenberg, Kurt-Mothes-Strasse 3a, 06120 Halle/Saale,
Germany
| | - David C. Schriemer
- Department of Biochemistry & Molecular Biology, Robson DNA
Science Centre, University of Calgary, 3330 Hospital Drive North West, Calgary,
Alberta T2N 4N1, Canada
| | - Yi Shi
- Department of Cell Biology, University of Pittsburgh, School of
Medicine, Pittsburgh, Pennsylvania 15213, United States
| | - J. Mark Skehel
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus,
Francis Crick Avenue, Cambridge CB2 0QH, U.K
| | - Moriya Slavin
- Department of Biological Chemistry, The Alexander Silberman
Institute of Life Sciences, Safra Campus Givat Ram, The Hebrew University of
Jerusalem, Jerusalem 91904, Israel
| | - Frank Sobott
- Department of Chemistry, University of Antwerp, Groenenborgerlaan
171, 2020 Antwerp, Belgium
- The Astbury Centre for Structural Molecular Biology and School of
Molecular and Cellular Biology, University of Leeds, LS2 9JT Leeds, U.K
| | - Victor Solis-Mezarino
- Gene Center Munich, Department of Biochemistry, Faculty of Chemistry
and Pharmacy, Ludwig Maximilians University of Munich, Feodor-Lynen-Strasse 25,
81377 Munich, Germany
| | - Heike Stephanowitz
- Leibniz Institute of Molecular Pharmacology (FMP),
Robert-Rössle-Strasse 10, 13125 Berlin, Germany
| | - Florian Stengel
- University of Konstanz, Department of Biology,
Universitätsstrasse 10, 78457 Konstanz, Germany
| | - Christian E. Stieger
- Protein Chemistry Facility, Research Institute of Molecular
Pathology (IMP) and Institute of Molecular Biotechnology (IMBA), Vienna Biocenter
(VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Esben Trabjerg
- Department of Pharmacy, University of Copenhagen, 2100 Copenhagen,
Denmark
| | - Michael Trnka
- UCSF Mass Spectrometry Facility, Genentech Hall, 600 16th Street,
San Francisco, California 94158, United States
| | - Marta Vilaseca
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona
Institute of Science and Technology (BIST), Baldiri Reixac 10, 08028 Barcelona,
Spain
| | - Rosa Viner
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose,
California 95134, United States
| | - Yufei Xiang
- Department of Cell Biology, University of Pittsburgh, School of
Medicine, Pittsburgh, Pennsylvania 15213, United States
| | - Sule Yilmaz
- Computational Systems Biochemistry Research Group,
Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried,
Germany
| | - Alex Zelter
- Department of Biochemistry, University of Washington, Seattle,
Washington 98195, United States
| | - Daniel Ziemianowicz
- Department of Biochemistry & Molecular Biology, Robson DNA
Science Centre, University of Calgary, 3330 Hospital Drive North West, Calgary,
Alberta T2N 4N1, Canada
| | - Alexander Leitner
- Department of Biology, Institute of Molecular Systems Biology, ETH
Zurich, Otto-Stern-Weg 3, 8093 Zurich, Switzerland
| | - Andrea Sinz
- Department of Pharmaceutical Chemistry and Bioanalytics, Institute
of Pharmacy, Charles Tanford Protein Center, Martin Luther University
Halle-Wittenberg, Kurt-Mothes-Strasse 3a, 06120 Halle/Saale, Germany
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308
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Carne NA, Bell S, Brown AP, Määttä A, Flagler MJ, Benham AM. Reductive Stress Selectively Disrupts Collagen Homeostasis and Modifies Growth Factor-independent Signaling Through the MAPK/Akt Pathway in Human Dermal Fibroblasts. Mol Cell Proteomics 2019; 18:1123-1137. [PMID: 30890563 PMCID: PMC6553930 DOI: 10.1074/mcp.ra118.001140] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 03/15/2019] [Indexed: 01/03/2023] Open
Abstract
Redox stress is a well-known contributor to aging and diseases in skin. Reductants such as dithiothreitol (DTT) can trigger a stress response by disrupting disulfide bonds. However, the quantitative response of the cellular proteome to reductants has not been explored, particularly in cells such as fibroblasts that produce extracellular matrix proteins. Here, we have used a robust, unbiased, label-free SWATH-MS proteomic approach to quantitate the response of skin fibroblast cells to DTT in the presence or absence of the growth factor PDGF. Of the 4487 proteins identified, only 42 proteins showed a statistically significant change of 2-fold or more with reductive stress. Our proteomics data show that reductive stress results in the loss of a small subset of reductant-sensitive proteins (including the collagens COL1A1/2 and COL3A1, and the myopathy-associated collagens COL6A1/2/3), and the down-regulation of targets downstream of the MAPK pathway. We show that a reducing environment alters signaling through the PDGF-associated MAPK/Akt pathways, inducing chronic dephosphorylation of ERK1/2 at Thr202/Tyr204 and phosphorylation of Akt at Ser473 in a growth factor-independent manner. Our data highlights collagens as sentinel molecules for redox stress downstream of MAPK/Akt, and identifies intervention points to modulate the redox environment to target skin diseases and conditions associated with erroneous matrix deposition.
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Affiliation(s)
- Naomi A Carne
- From the ‡The Department of Biosciences, Durham University, Stockton Road, Durham, DH1 3LE, UK
| | - Steven Bell
- From the ‡The Department of Biosciences, Durham University, Stockton Road, Durham, DH1 3LE, UK
| | - Adrian P Brown
- From the ‡The Department of Biosciences, Durham University, Stockton Road, Durham, DH1 3LE, UK
| | - Arto Määttä
- From the ‡The Department of Biosciences, Durham University, Stockton Road, Durham, DH1 3LE, UK
| | - Michael J Flagler
- §The Procter & Gamble Company, 8700 Mason Montgomery Road, Mason, OH 45040
| | - Adam M Benham
- From the ‡The Department of Biosciences, Durham University, Stockton Road, Durham, DH1 3LE, UK;
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309
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Giudice G, Petsalaki E. Proteomics and phosphoproteomics in precision medicine: applications and challenges. Brief Bioinform 2019; 20:767-777. [PMID: 29077858 PMCID: PMC6585152 DOI: 10.1093/bib/bbx141] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Revised: 09/21/2017] [Indexed: 12/11/2022] Open
Abstract
Recent advances in proteomics allow the accurate measurement of abundances for thousands of proteins and phosphoproteins from multiple samples in parallel. Therefore, for the first time, we have the opportunity to measure the proteomic profiles of thousands of patient samples or disease model cell lines in a systematic way, to identify the precise underlying molecular mechanism and discover personalized biomarkers, networks and treatments. Here, we review examples of successful use of proteomics and phosphoproteomics data sets in as well as their integration other omics data sets with the aim of precision medicine. We will discuss the bioinformatics challenges posed by the generation, analysis and integration of such large data sets and present potential reasons why proteomics profiling and biomarkers are not currently widely used in the clinical setting. We will finally discuss ways to contribute to the better use of proteomics data in precision medicine and the clinical setting.
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Affiliation(s)
- Girolamo Giudice
- European Molecular Biology Laboratory European Bioinformatics Institute
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310
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Wang G, Meyer JG, Cai W, Softic S, Li ME, Verdin E, Newgard C, Schilling B, Kahn CR. Regulation of UCP1 and Mitochondrial Metabolism in Brown Adipose Tissue by Reversible Succinylation. Mol Cell 2019; 74:844-857.e7. [PMID: 31000437 PMCID: PMC6525068 DOI: 10.1016/j.molcel.2019.03.021] [Citation(s) in RCA: 118] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 02/06/2019] [Accepted: 03/20/2019] [Indexed: 11/23/2022]
Abstract
Brown adipose tissue (BAT) is rich in mitochondria and plays important roles in energy expenditure, thermogenesis, and glucose homeostasis. We find that levels of mitochondrial protein succinylation and malonylation are high in BAT and subject to physiological and genetic regulation. BAT-specific deletion of Sirt5, a mitochondrial desuccinylase and demalonylase, results in dramatic increases in global protein succinylation and malonylation. Mass spectrometry-based quantification of succinylation reveals that Sirt5 regulates the key thermogenic protein in BAT, UCP1. Mutation of the two succinylated lysines in UCP1 to acyl-mimetic glutamine and glutamic acid significantly decreases its stability and activity. The reduced function of UCP1 and other proteins in Sirt5KO BAT results in impaired mitochondria respiration, defective mitophagy, and metabolic inflexibility. Thus, succinylation of UCP1 and other mitochondrial proteins plays an important role in BAT and in regulation of energy homeostasis.
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Affiliation(s)
- GuoXiao Wang
- Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, USA
| | - Jesse G Meyer
- Buck Institute for Research on Aging, Novato, CA 94945, USA
| | - Weikang Cai
- Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, USA
| | - Samir Softic
- Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, USA
| | - Mengyao Ella Li
- Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, USA
| | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA 94945, USA
| | - Christopher Newgard
- Sarah W. Stedman Nutrition and Metabolism Center and Duke Molecular Physiology Institute, Departments of Pharmacology and Cancer Biology and Medicine, Duke University Medical Center, Durham, NC 27708, USA
| | | | - C Ronald Kahn
- Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, USA.
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311
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A new class of protein biomarkers based on subcellular distribution: application to a mouse liver cancer model. Sci Rep 2019; 9:6913. [PMID: 31061415 PMCID: PMC6502816 DOI: 10.1038/s41598-019-43091-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Accepted: 04/15/2019] [Indexed: 12/18/2022] Open
Abstract
To-date, most proteomic studies aimed at discovering tissue-based cancer biomarkers have compared the quantity of selected proteins between case and control groups. However, proteins generally function in association with other proteins to form modules localized in particular subcellular compartments in specialized cell types and tissues. Sub-cellular mislocalization of proteins has in fact been detected as a key feature in a variety of cancer cells. Here, we describe a strategy for tissue-biomarker detection based on a mitochondrial fold enrichment (mtFE) score, which is sensitive to protein abundance changes as well as changes in subcellular distribution between mitochondria and cytosol. The mtFE score integrates protein abundance data from total cellular lysates and mitochondria-enriched fractions, and provides novel information for the classification of cancer samples that is not necessarily apparent from conventional abundance measurements alone. We apply this new strategy to a panel of wild-type and mutant mice with a liver-specific gene deletion of Liver receptor homolog 1 (Lrh-1hep−/−), with both lines containing control individuals as well as individuals with liver cancer induced by diethylnitrosamine (DEN). Lrh-1 gene deletion attenuates cancer cell metabolism in hepatocytes through mitochondrial glutamine processing. We show that proteome changes based on mtFE scores outperform protein abundance measurements in discriminating DEN-induced liver cancer from healthy liver tissue, and are uniquely robust against genetic perturbation. We validate the capacity of selected proteins with informative mtFE scores to indicate hepatic malignant changes in two independent mouse models of hepatocellular carcinoma (HCC), thus demonstrating the robustness of this new approach to biomarker research. Overall, the method provides a novel, sensitive approach to cancer biomarker discovery that considers contextual information of tested proteins.
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312
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Vincent RM, Wright BW, Jaschke PR. Measuring Amber Initiator tRNA Orthogonality in a Genomically Recoded Organism. ACS Synth Biol 2019; 8:675-685. [PMID: 30856316 DOI: 10.1021/acssynbio.9b00021] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Using engineered initiator tRNA for precise control of protein translation within cells has great promise within future orthogonal translation systems to decouple housekeeping protein metabolism from that of engineered genetic systems. Previously, E. coli strain C321.ΔA. exp lacking all UAG stop codons was created, freeing this "amber" stop codon for other purposes. An engineered "amber initiator" tRNACUAfMet that activates translation at UAG codons is available, but little is known about this tRNA's orthogonality. Here, we combine for the first time the amber initiator tRNACUAfMet in C321.ΔA. exp and measure its cellular effects. We found that the tRNACUAfMet expression resulted in a nearly 200-fold increase in fluorescent reporter expression with a unimodal population distribution and no apparent cellular fitness defects. Proteomic analysis revealed upregulated ribosome-associated, tRNA degradation, and amino acid biosynthetic proteins, with no evidence for off-target translation initiation. In contrast to previous work, we show that UAG-initiated proteins carry N-terminal methionine, but have no evidence for glutamine. Together, our results identify beneficial features of using the amber initiator tRNACUAfMet to control gene expression while also revealing fundamental challenges to using engineered initiator tRNAs as the basis for orthogonal translation initiation systems.
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Affiliation(s)
- Russel M. Vincent
- Department of Molecular Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Bradley W. Wright
- Department of Molecular Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Paul R. Jaschke
- Department of Molecular Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
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313
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DeLaney K, Li L. Data Independent Acquisition Mass Spectrometry Method for Improved Neuropeptidomic Coverage in Crustacean Neural Tissue Extracts. Anal Chem 2019; 91:5150-5158. [PMID: 30888792 PMCID: PMC6481171 DOI: 10.1021/acs.analchem.8b05734] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Neuropeptides are an important class of signaling molecules in the nervous and neuroendocrine system, but they are challenging to study due to their low concentration in vivo in the presence of numerous interfering artifacts. Often the limitation of mass spectrometry analyses of neuropeptides in complex tissue extracts is not due to neuropeptides being below the detection limit but due to ions not being selected for tandem mass spectrometry during the liquid chromatography elution time and therefore not being identified. In this study, a data independent acquisition (DIA) method was developed to improve the coverage of neuropeptides in neural tissue from the model organism C. borealis. The optimal mass-to-charge ratio range and isolation window were determined and subsequently used to detect more neuropeptides in extracts from the brain and pericardial organs than the conventional data dependent acquisition method. The DIA method led to the detection of almost twice as many neuropeptides in the brain and approximately 1.5-fold more neuropeptides in the pericardial organs. The technical and biological reproducibility were also explored and found to be improved over the original method, with 56% of neuropeptides detected in 3 out of 3 replicate injections and 62% in 3 out of 3 biological replicates. Furthermore, 68 putative novel neuropeptides were detected and identified with de novo sequencing. The quantitative accuracy of the method was also explored. The developed method is anticipated to be useful for gaining a deeper profiling of neuropeptides, especially those in low abundance, in a variety of sample types.
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Affiliation(s)
- Kellen DeLaney
- Department of Chemistry, University of Wisconsin–Madison, 1101 University Avenue, Madison, Wisconsin 53706-1322, United States
| | - Lingjun Li
- Department of Chemistry, University of Wisconsin–Madison, 1101 University Avenue, Madison, Wisconsin 53706-1322, United States
- School of Pharmacy, University of Wisconsin–Madison, 5125 Rennebohm Hall, 777 Highland Avenue, Madison, Wisconsin 53705-2222, United States
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314
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Masuda T, Hoshiyama T, Uemura T, Hirayama-Kurogi M, Ogata S, Furukawa A, Couraud PO, Furihata T, Ito S, Ohtsuki S. Large-Scale Quantitative Comparison of Plasma Transmembrane Proteins between Two Human Blood–Brain Barrier Model Cell Lines, hCMEC/D3 and HBMEC/ciβ. Mol Pharm 2019; 16:2162-2171. [DOI: 10.1021/acs.molpharmaceut.9b00114] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Takeshi Masuda
- AMED-CREST, Japan Agency for Medical Research and Development, 1-7-1 Otemachi, Chiyoda, Tokyo 100-0004, Japan
| | | | | | | | | | | | - Pierre-Olivier Couraud
- Institut Cochin, Paris Descartes University, Inserm U1016, CNRS UMR8104, Paris 75014, France
| | - Tomomi Furihata
- Department of Pharmacology, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba-shi, Chiba 260-8670 Japan
| | - Shingo Ito
- AMED-CREST, Japan Agency for Medical Research and Development, 1-7-1 Otemachi, Chiyoda, Tokyo 100-0004, Japan
| | - Sumio Ohtsuki
- AMED-CREST, Japan Agency for Medical Research and Development, 1-7-1 Otemachi, Chiyoda, Tokyo 100-0004, Japan
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315
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Global Lysine Acetylation in Escherichia coli Results from Growth Conditions That Favor Acetate Fermentation. J Bacteriol 2019; 201:JB.00768-18. [PMID: 30782634 DOI: 10.1128/jb.00768-18] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 02/11/2019] [Indexed: 01/17/2023] Open
Abstract
Lysine acetylation is thought to provide a mechanism for regulating metabolism in diverse bacteria. Indeed, many studies have shown that the majority of enzymes involved in central metabolism are acetylated and that acetylation can alter enzyme activity. However, the details regarding this regulatory mechanism are still unclear, specifically with regard to the signals that induce lysine acetylation. To better understand this global regulatory mechanism, we profiled changes in lysine acetylation during growth of Escherichia coli on the hexose glucose or the pentose xylose at both high and low sugar concentrations using label-free mass spectrometry. The goal was to see whether lysine acetylation differed during growth on these two different sugars. No significant differences, however, were observed. Rather, the initial sugar concentration was the principal factor governing changes in lysine acetylation, with higher sugar concentrations causing more acetylation. These results suggest that acetylation does not target specific metabolic pathways but rather simply targets accessible lysines, which may or may not alter enzyme activity. They further suggest that lysine acetylation principally results from conditions that favor accumulation of acetyl phosphate, the principal acetate donor in E. coli IMPORTANCE Bacteria alter their metabolism in response to nutrient availability, growth conditions, and environmental stresses using a number of different mechanisms. One is lysine acetylation, a posttranslational modification known to target many metabolic enzymes. However, little is known about this regulatory mode. We investigated the factors inducing changes in lysine acetylation by comparing growth on glucose and xylose. We found that the specific sugar used for growth did not alter the pattern of acetylation; rather, the amount of sugar did, with more sugar causing more acetylation. These results imply that lysine acetylation is a global regulatory mechanism that is responsive not to the specific carbon source per se but rather to the accumulation of downstream metabolites.
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316
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Grabowski P, Hesse S, Hollizeck S, Rohlfs M, Behrends U, Sherkat R, Tamary H, Ünal E, Somech R, Patıroğlu T, Canzar S, van der Werff Ten Bosch J, Klein C, Rappsilber J. Proteome Analysis of Human Neutrophil Granulocytes From Patients With Monogenic Disease Using Data-independent Acquisition. Mol Cell Proteomics 2019; 18:760-772. [PMID: 30630937 PMCID: PMC6442368 DOI: 10.1074/mcp.ra118.001141] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 12/14/2018] [Indexed: 11/06/2022] Open
Abstract
Neutrophil granulocytes are critical mediators of innate immunity and tissue regeneration. Rare diseases of neutrophil granulocytes may affect their differentiation and/or functions. However, there are very few validated diagnostic tests assessing the functions of neutrophil granulocytes in these diseases. Here, we set out to probe omics analysis as a novel diagnostic platform for patients with defective differentiation and function of neutrophil granulocytes. We analyzed highly purified neutrophil granulocytes from 68 healthy individuals and 16 patients with rare monogenic diseases. Cells were isolated from fresh venous blood (purity >99%) and used to create a spectral library covering almost 8000 proteins using strong cation exchange fractionation. Patient neutrophil samples were then analyzed by data-independent acquisition proteomics, quantifying 4154 proteins in each sample. Neutrophils with mutations in the neutrophil elastase gene ELANE showed large proteome changes that suggest these mutations may affect maturation of neutrophil granulocytes and initiate misfolded protein response and cellular stress mechanisms. In contrast, only few proteins changed in patients with leukocyte adhesion deficiency (LAD) and chronic granulomatous disease (CGD). Strikingly, neutrophil transcriptome analysis showed no correlation with its proteome. In case of two patients with undetermined genetic causes, proteome analysis guided the targeted genetic diagnostics and uncovered the underlying genomic mutations. Data-independent acquisition proteomics may help to define novel pathomechanisms in neutrophil diseases and provide a clinically useful diagnostic dimension.
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Affiliation(s)
- Piotr Grabowski
- From the ‡Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Sebastian Hesse
- §Dr. von Hauner Children's Hospital, Department of Pediatrics, University Hospital, LMU Munich, 80337 Munich, Germany
| | - Sebastian Hollizeck
- §Dr. von Hauner Children's Hospital, Department of Pediatrics, University Hospital, LMU Munich, 80337 Munich, Germany
| | - Meino Rohlfs
- §Dr. von Hauner Children's Hospital, Department of Pediatrics, University Hospital, LMU Munich, 80337 Munich, Germany
| | - Uta Behrends
- ‖Children's Hospital, Hematology-Oncology, Technical University Munich, 80804 Munich, Germany
| | - Roya Sherkat
- Acquired Immunodeficiency Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Hannah Tamary
- Schneider Children's Medical Center of Israel, Petah Tikva, Sackler School of Medicine, Tel Aviv University, Israel
| | - Ekrem Ünal
- Department of Pediatrics, Division of Pediatric Hematology & Oncology, Erciyes University, Kayseri, Turkey
| | - Raz Somech
- Pediatric Department A and Immunology Service, Jeffrey Modell Foundation Center, Edmond and Lily Safra Children's Hospital, Sheba Medical Center, Tel Hashomer, Sackler Faculty of Medicine, Tel Aviv University Tel Aviv, Israel
| | - Türkan Patıroğlu
- Department of Pediatrics, Division of Pediatric Hematology & Oncology, Erciyes University, Kayseri, Turkey
| | - Stefan Canzar
- Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany
| | | | - Christoph Klein
- §Dr. von Hauner Children's Hospital, Department of Pediatrics, University Hospital, LMU Munich, 80337 Munich, Germany;.
| | - Juri Rappsilber
- From the ‡Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany;; ¶Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK;.
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317
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Label-free absolute protein quantification with data-independent acquisition. J Proteomics 2019; 200:51-59. [PMID: 30880166 DOI: 10.1016/j.jprot.2019.03.005] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 02/19/2019] [Accepted: 03/06/2019] [Indexed: 02/05/2023]
Abstract
Despite data-independent acquisition (DIA) has been increasingly used for relative protein quantification, DIA-based label-free absolute quantification method has not been fully established. Here we present a novel DIA method using the TPA algorithm (DIA-TPA) for the absolute quantification of protein expressions in human liver microsomal and S9 samples. To validate this method, both data-dependent acquisition (DDA) and DIA experiments were conducted on 36 individual human liver microsome and S9 samples. The MS2-based DIA-TPA was able to quantify approximately twice as many proteins as the MS1-based DDA-TPA method, whereas protein concentrations determined by the two approaches were comparable. To evaluate the accuracy of the DIA-TPA method, we absolutely quantified carboxylesterase 1 concentrations in human liver S9 fractions using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-TPA analysis. Finally, we employed a unique algorithm in DIA-TPA to distribute the MS signals from shared peptides to individual proteins or isoforms and successfully applied the method to the absolute quantification of several drug-metabolizing enzymes in human liver microsomes. In sum, the DIA-TPA method not only can absolutely quantify entire proteomes and specific proteins, but also has the capability quantifying proteins with shared peptides. SIGNIFICANCE: Data independent acquisition (DIA) has emerged as a powerful approach for relative protein quantification at the whole proteome level. However, DIA-based label-free absolute protein quantification (APQ) method has not been fully established. In the present study, we present a novel DIA-based label-free APQ approach, named DIA-TPA, with the capability absolutely quantifying proteins with shared peptides. The method was validated by comparing the quantification results of DIA-TPA with that obtained from stable isotope-labeled internal standard-based proteomic assays.
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318
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Tong Y, Ku X, Wu C, Liu J, Yang C, Tang W, Yan W, Tang J. Data-independent acquisition-based quantitative proteomic analysis reveals differences in host immune response of peripheral blood mononuclear cells to sepsis. Scand J Immunol 2019; 89:e12748. [PMID: 30667541 DOI: 10.1111/sji.12748] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 12/24/2018] [Accepted: 01/08/2019] [Indexed: 01/19/2023]
Abstract
This study was aimed to uncover proteins that are differentially expressed in sepsis. Data-independent acquisition (DIA) was used for analysis to identify differentially expressed proteins in peripheral blood mononuclear cells (PBMCs) of patients. A total of 24 non-septic intensive care unit (ICU) patients, 11 septic shock patients and 27 patients diagnosed with sepsis were recruited for the mass spectrometry (MS) discovery. PBMCs were isolated from routine blood samples and digested into peptides. A DIA workflow was developed using a quadrupole-Orbitrap liquid chromatography LC-MS system, and mass spectra peaks were extracted by Skyline software. Orthogonal partial least-squares discriminant analysis (OPLS-DA) and partial least-squares discriminant analysis (PLS-DA) were applied to distinguish the patient groups at the level of fragment ion and peptide. Differentially expressed proteins in the patient groups were verified by enzyme-linked immunosorbent assay (ELISA). Receiver-operating characteristic (ROC) curves were used to evaluate the protein expression. A total of 1062 fragment ions and 122 proteins were identified in the MS-DIA analysis conducted by Skyline software. Using gene ontology clustering analysis, we discovered that 51 of the 122 identified proteins were associated with biological processes, including carbon metabolism, biosynthesis of antibiotics, platelet activation, bacterial invasion of epithelial cells and complement, and coagulation cascades. Among them, five proteins (high-mobility group box1 [HMGB1], matrix metalloproteinase 8 [MMP8], neutrophil gelatinase-associated lipocalin [NGAL], lactotransferrin [LTF] and grancalcin [GCA]) were identified by ELISA as closely related to the development of sepsis. The ROC curves displayed good sensitivity and specificity.
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Affiliation(s)
- Yiqing Tong
- Department of Trauma-Emergency & Critical Care Medicine, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
| | - Xin Ku
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chunrong Wu
- Department of Trauma-Emergency & Critical Care Medicine, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
| | - Jianjun Liu
- Department of Trauma-Emergency & Critical Care Medicine, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
| | - Chunhui Yang
- Department of Trauma-Emergency & Critical Care Medicine, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
| | | | - Wei Yan
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jianguo Tang
- Department of Trauma-Emergency & Critical Care Medicine, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China
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319
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Chen Y, Vu J, Thompson MG, Sharpless WA, Chan LJG, Gin JW, Keasling JD, Adams PD, Petzold CJ. A rapid methods development workflow for high-throughput quantitative proteomic applications. PLoS One 2019; 14:e0211582. [PMID: 30763335 PMCID: PMC6375547 DOI: 10.1371/journal.pone.0211582] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 01/16/2019] [Indexed: 12/13/2022] Open
Abstract
Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes.
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Affiliation(s)
- Yan Chen
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Jonathan Vu
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Mitchell G. Thompson
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, United States of America
| | - William A. Sharpless
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Leanne Jade G. Chan
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Jennifer W. Gin
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Jay D. Keasling
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
- Department of Bioengineering, University of California Berkeley, Berkeley, CA, United States of America
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA, United States of America
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
| | - Paul D. Adams
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Department of Bioengineering, University of California Berkeley, Berkeley, CA, United States of America
- Molecular Biophysics and Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - Christopher J. Petzold
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
- * E-mail:
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320
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Generation of a zebrafish SWATH-MS spectral library to quantify 10,000 proteins. Sci Data 2019; 6:190011. [PMID: 30747917 PMCID: PMC6371892 DOI: 10.1038/sdata.2019.11] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 12/17/2018] [Indexed: 12/12/2022] Open
Abstract
Sequential window acquisition of all theoretical mass spectra (SWATH-MS) requires a spectral library to extract quantitative measurements from the mass spectrometry data acquired in data-independent acquisition mode (DIA). Large combined spectral libraries containing SWATH assays have been generated for humans and several other organisms, but so far no publicly available library exists for measuring the proteome of zebrafish, a rapidly emerging model system in biomedical research. Here, we present a large zebrafish SWATH spectral library to measure the abundance of 104,185 proteotypic peptides from 10,405 proteins. The library includes proteins expressed in 9 different zebrafish tissues (brain, eye, heart, intestine, liver, muscle, ovary, spleen, and testis) and provides an important new resource to quantify 40% of the protein-coding zebrafish genes. We employ this resource to quantify the proteome across brain, muscle, and liver and characterize divergent expression levels of paralogous proteins in different tissues. Data are available via ProteomeXchange (PXD010876, PXD010869) and SWATHAtlas (PASS01237).
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321
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Murphy S, Dowling P, Zweyer M, Swandulla D, Ohlendieck K. Proteomic profiling of giant skeletal muscle proteins. Expert Rev Proteomics 2019; 16:241-256. [DOI: 10.1080/14789450.2019.1575205] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Affiliation(s)
- Sandra Murphy
- Department of Biology, Maynooth University, National University of Ireland, Maynooth, Ireland
- Newcastle Fibrosis Research Group, Institute of Cellular Medicine, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Paul Dowling
- Department of Biology, Maynooth University, National University of Ireland, Maynooth, Ireland
| | - Margit Zweyer
- Institute of Physiology II, University of Bonn, Bonn, Germany
| | | | - Kay Ohlendieck
- Department of Biology, Maynooth University, National University of Ireland, Maynooth, Ireland
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322
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Wu W, Dai RT, Bendixen E. Comparing SRM and SWATH Methods for Quantitation of Bovine Muscle Proteomes. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2019; 67:1608-1618. [PMID: 30624930 DOI: 10.1021/acs.jafc.8b05459] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Mass spectrometry (MS) has become essential for efficient and accurate quantification of proteins and proteomes and, thus, a key technology throughout all biosciences. However, validated MS methods are still scarce for meat quality research applications. The objective of this work was to develop and compare two targeted proteomic methods, namely, selected reaction monitoring (SRM) and sequential window acquisition of all theoretical spectra (SWATH), for the quantification of 11 bovine muscle proteins that may be indicators of meat color. Both methods require evaluation of spectra from proteotypic and quantotypic peptides, and we here report our evaluation of which peptides and MS parameters are best suited for robust quantification of these 11 proteins. We observed that the SRM approach provides better reproducibility, linearity, and sensitivity than SWATH and is therefore ideal for targeted quantification of low-abundance proteins, while the SWATH approach provides a more time-efficient method for targeted protein quantification of high-abundance proteins and, additionally, supports the search for novel biomarkers.
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Affiliation(s)
- Wei Wu
- College of Food Science and Nutritional Engineering , China Agricultural University , No. 17 Qinghua East Road , Haidian District, Beijing 100083 , P. R. China
- Department of Molecular Biology and Genetics, Faculty of Science and Technology , Aarhus University , Gustav Wieds Vej 10 , 8000 Aarhus , Denmark
| | - Rui-Tong Dai
- College of Food Science and Nutritional Engineering , China Agricultural University , No. 17 Qinghua East Road , Haidian District, Beijing 100083 , P. R. China
| | - Emøke Bendixen
- Department of Molecular Biology and Genetics, Faculty of Science and Technology , Aarhus University , Gustav Wieds Vej 10 , 8000 Aarhus , Denmark
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323
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Rice SJ, Liu X, Zhang J, Belani CP. Absolute Quantification of All Identified Plasma Proteins from SWATH Data for Biomarker Discovery. Proteomics 2019; 19:e1800135. [DOI: 10.1002/pmic.201800135] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 09/27/2018] [Indexed: 02/05/2023]
Affiliation(s)
- Shawn J. Rice
- Penn State Cancer InstitutePenn State College of Medicine Hershey PA 17033 USA
| | - Xin Liu
- Penn State Cancer InstitutePenn State College of Medicine Hershey PA 17033 USA
| | - Jianhong Zhang
- Penn State Cancer InstitutePenn State College of Medicine Hershey PA 17033 USA
| | - Chandra P. Belani
- Penn State Cancer InstitutePenn State College of Medicine Hershey PA 17033 USA
- Department of MedicinePenn State College of Medicine Hershey PA 17033 USA
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324
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Heusel M, Bludau I, Rosenberger G, Hafen R, Frank M, Banaei-Esfahani A, van Drogen A, Collins BC, Gstaiger M, Aebersold R. Complex-centric proteome profiling by SEC-SWATH-MS. Mol Syst Biol 2019; 15:e8438. [PMID: 30642884 PMCID: PMC6346213 DOI: 10.15252/msb.20188438] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper, we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction, and the computational framework CCprofiler to detect and quantify protein complexes by error‐controlled, complex‐centric analysis using prior information from generic protein interaction maps. Our analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2,127 protein subunits. The technique identifies novel sub‐complexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible and provide a web platform, SECexplorer, for custom exploration of the HEK293 proteome modularity.
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Affiliation(s)
- Moritz Heusel
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.,PhD Program in Molecular and Translational Biomedicine of the Competence Center Personalized Medicine UZH/ETH, Zurich, Switzerland
| | - Isabell Bludau
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.,PhD Program in Systems Biology, Life Science Zurich Graduate School, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - George Rosenberger
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Robin Hafen
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.,Department of Computer Science, ETH Zurich, Zurich, Switzerland
| | - Max Frank
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Amir Banaei-Esfahani
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.,PhD Program in Systems Biology, Life Science Zurich Graduate School, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Audrey van Drogen
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Ben C Collins
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Matthias Gstaiger
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland .,Faculty of Science, University of Zurich, Zurich, Switzerland
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325
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Anania VG, Yu K, Pingitore F, Li Q, Rose CM, Liu P, Sandoval W, Herman AE, Lill JR, Mathews WR. Discovery and Qualification of Candidate Urinary Biomarkers of Disease Activity in Lupus Nephritis. J Proteome Res 2019; 18:1264-1277. [PMID: 30525646 DOI: 10.1021/acs.jproteome.8b00874] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Lupus nephritis (LN) is a severe clinical manifestation of systemic lupus erythematosus (SLE) associated with significant morbidity and mortality. Assessment of severity and activity of renal involvement in SLE requires a kidney biopsy, an invasive procedure with limited prognostic value. Noninvasive biomarkers are needed to inform treatment decisions and to monitor disease activity. Proteinuria is associated with disease progression in LN; however, the composition of the LN urinary proteome remains incompletely characterized. To address this, we profiled LN urine samples using complementary mass spectrometry-based methods: protein gel fractionation, chemical labeling using tandem mass tags, and data-independent acquisition. Combining results from these approaches yielded quantitative information on 2573 unique proteins in urine from LN patients. A multiple-reaction monitoring (MRM) method was established to confirm eight proteins in an independent cohort of LN patients, and seven proteins (transferrin, α-2-macroglobulin, haptoglobin, afamin, α-1-antitrypsin, vimentin, and ceruloplasmin) were confirmed to be elevated in LN urine compared to healthy controls. In this study, we demonstrate that deep mass spectrometry profiling of a small number of patient samples can identify high-quality biomarkers that replicate in an independent LN disease cohort. These biomarkers are being used to inform clinical biomarker strategies to support longitudinal and interventional studies focused on evaluating disease progression and treatment efficacy of novel LN therapeutics.
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326
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Orlando E, Aebersold R. On the contribution of mass spectrometry-based platforms to the field of personalized oncology. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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327
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Abstract
The mechanism underlying many biological phenotypes remains unknown despite the increasing availability of whole genome and transcriptome sequencing. Direct measurement of changes in protein expression is an attractive alternative and has the potential to reveal novel processes. Mass spectrometry has become the standard method for proteomics, allowing both the confident identification and quantification of thousands of proteins from biological samples. In this review, mass spectrometry-based proteomic methods and their applications are described.
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Affiliation(s)
- J Robert O'Neill
- Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK. Robert.o'.,Department of Clinical Surgery, Royal Infirmary of Edinburgh, Edinburgh, UK. Robert.o'
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328
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Abstract
The varied landscape of the adaptive immune response is determined by the peptides presented by immune cells, derived from viral or microbial pathogens or cancerous cells. The study of immune biomarkers or antigens is not new, and classical methods such as agglutination, enzyme-linked immunosorbent assay, or Western blotting have been used for many years to study the immune response to vaccination or disease. However, in many of these traditional techniques, protein or peptide identification has often been the bottleneck. Recent progress in genomics and mass spectrometry have led to many of the rapid advances in proteomics approaches. Immunoproteomics describes a rapidly growing collection of approaches that have the common goal of identifying and measuring antigenic peptides or proteins. This includes gel-based, array-based, mass spectrometry-based, DNA-based, or in silico approaches. Immunoproteomics is yielding an understanding of disease and disease progression, vaccine candidates, and biomarkers. This review gives an overview of immunoproteomics and closely related technologies that are used to define the full set of protein antigens targeted by the immune system during disease.
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Affiliation(s)
- Kelly M Fulton
- Human Health Therapeutics Research Centre, National Research Council of Canada, Ottawa, ON, Canada
| | - Isabel Baltat
- Human Health Therapeutics Research Centre, National Research Council of Canada, Ottawa, ON, Canada
| | - Susan M Twine
- Human Health Therapeutics Research Centre, National Research Council of Canada, Ottawa, ON, Canada.
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329
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Muntel J, Gandhi T, Verbeke L, Bernhardt OM, Treiber T, Bruderer R, Reiter L. Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy. Mol Omics 2019; 15:348-360. [DOI: 10.1039/c9mo00082h] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Optimization of chromatography and data analysis resulted in more than 10 000 proteins in a single shot at a validated FDR of 1% (two-species test) and revealed deep insights into the testis cancer physiology.
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330
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Yang Y, Zeng B, Sun Z, Esfahani AM, Hou J, Jiao ND, Liu L, Chen L, Basson MD, Dong L, Yang R, Xi N. Optimization of Protein-Protein Interaction Measurements for Drug Discovery Using AFM Force Spectroscopy. IEEE TRANSACTIONS ON NANOTECHNOLOGY 2019; 18:509-517. [PMID: 32051682 PMCID: PMC7015265 DOI: 10.1109/tnano.2019.2915507] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Increasingly targeted in drug discovery, protein-protein interactions challenge current high throughput screening technologies in the pharmaceutical industry. Developing an effective and efficient method for screening small molecules or compounds is critical to accelerate the discovery of ligands for enzymes, receptors and other pharmaceutical targets. Here, we report developments of methods to increase the signal-to-noise ratio (SNR) for screening protein-protein interactions using atomic force microscopy (AFM) force spectroscopy. We have demonstrated the effectiveness of these developments on detecting the binding process between focal adhesion kinases (FAK) with protein kinase B (Akt1), which is a target for potential cancer drugs. These developments include optimized probe and substrate functionalization processes and redesigned probe-substrate contact regimes. Furthermore, a statistical-based data processing method was developed to enhance the contrast of the experimental data. Collectively, these results demonstrate the potential of the AFM force spectroscopy in automating drug screening with high throughput.
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Affiliation(s)
- Yongliang Yang
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48823, USA
| | - Bixi Zeng
- Departments of Surgery and Biomedical Sciences, University of North Dakota, Grand Forks, ND, 58202, USA
| | - Zhiyong Sun
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48823, USA
| | - Amir Monemian Esfahani
- Department of Mechanical and Materials Engineering, University of Nebraska Lincoln, NE 68588 USA
| | - Jing Hou
- School of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China
| | - Nian-Dong Jiao
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110006, China
| | - Lianqing Liu
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110006, China
| | - Liangliang Chen
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48823, USA
| | - Marc D Basson
- Departments of Surgery and Biomedical Sciences, University of North Dakota, Grand Forks, ND, 58202, USA
| | - Lixin Dong
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48823, USA
| | - Ruiguo Yang
- Department of Mechanical and Materials Engineering, University of Nebraska Lincoln, NE 68588 USA
| | - Ning Xi
- Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48823, USA
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331
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Temporal dynamics of liver mitochondrial protein acetylation and succinylation and metabolites due to high fat diet and/or excess glucose or fructose. PLoS One 2018; 13:e0208973. [PMID: 30586434 PMCID: PMC6306174 DOI: 10.1371/journal.pone.0208973] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2018] [Accepted: 11/28/2018] [Indexed: 12/11/2022] Open
Abstract
Dietary macronutrient composition alters metabolism through several mechanisms, including post-translational modification (PTM) of proteins. To connect diet and molecular changes, here we performed short- and long-term feeding of mice with standard chow diet (SCD) and high-fat diet (HFD), with or without glucose or fructose supplementation, and quantified liver metabolites, 861 proteins, and 1,815 protein level-corrected mitochondrial acetylation and succinylation sites. Nearly half the acylation sites were altered by at least one diet; nutrient-specific changes in protein acylation sometimes encompass entire pathways. Although acetyl-CoA is an intermediate in both sugar and fat metabolism, acetyl-CoA had a dichotomous fate depending on its source; chronic feeding of dietary sugars induced protein hyperacetylation, whereas the same duration of HFD did not. Instead, HFD resulted in citrate accumulation, anaplerotic metabolism of amino acids, and protein hypo-succinylation. Together, our results demonstrate novel connections between dietary macronutrients, protein post-translational modifications, and regulation of fuel selection in liver.
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332
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Reubsaet L, Sweredoski MJ, Moradian A. Data-Independent Acquisition for the Orbitrap Q Exactive HF: A Tutorial. J Proteome Res 2018; 18:803-813. [DOI: 10.1021/acs.jproteome.8b00845] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Léon Reubsaet
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Department of Pharmaceutical Chemistry, School of Pharmacy, University of Oslo, Sem Sælands vei 3, N-0316 Oslo, Norway
| | - Michael J. Sweredoski
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Annie Moradian
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
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333
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Kim YJ, Sweet SMM, Egertson JD, Sedgewick AJ, Woo S, Liao WL, Merrihew GE, Searle BC, Vaske C, Heaton R, MacCoss MJ, Hembrough T. Data-Independent Acquisition Mass Spectrometry To Quantify Protein Levels in FFPE Tumor Biopsies for Molecular Diagnostics. J Proteome Res 2018; 18:426-435. [PMID: 30481034 DOI: 10.1021/acs.jproteome.8b00699] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Mass spectrometry-based protein quantitation is currently used to measure therapeutically relevant protein biomarkers in CAP/CLIA setting to predict likely responses of known therapies. Selected reaction monitoring (SRM) is the method of choice due to its outstanding analytical performance. However, data-independent acquisition (DIA) is now emerging as a proteome-scale clinical assay. We evaluated the ability of DIA to profile the patient-specific proteomes of sample-limited tumor biopsies and to quantify proteins of interest in a targeted fashion using formalin-fixed, paraffin-embedded (FFPE) tumor biopsies ( n = 12) selected from our clinical laboratory. DIA analysis on the tumor biopsies provided 3713 quantifiable proteins including actionable biomarkers currently in clinical use, successfully separated two gastric cancers from colorectal cancer specimen solely on the basis of global proteomic profiles, and identified subtype-specific proteins with prognostic or diagnostic value. We demonstrate the potential use of DIA-based quantitation to inform therapeutic decision-making using TUBB3, for which clinical cutoff expression levels have been established by SRM. Comparative analysis of DIA-based proteomic profiles and mRNA expression levels found positively and negatively correlated protein-gene pairs, a finding consistent with previously reported results from fresh-frozen tumor tissues.
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Affiliation(s)
- Yeoun Jin Kim
- NantOmics , 9600 Medical Center Drive , Rockville , Maryland 20850 , United States
| | - Steve M M Sweet
- NantOmics , 9600 Medical Center Drive , Rockville , Maryland 20850 , United States
| | - Jarrett D Egertson
- Department of Genome Sciences , University of Washington , 3720 15th Avenue NE , Seattle , Washington 98195 , United States
| | - Andrew J Sedgewick
- NantOmics , 2919 Mission Street , Santa Cruz , California 95060 , United States
| | - Sunghee Woo
- NantOmics , 9600 Medical Center Drive , Rockville , Maryland 20850 , United States
| | - Wei-Li Liao
- NantOmics , 9600 Medical Center Drive , Rockville , Maryland 20850 , United States
| | - Gennifer E Merrihew
- Department of Genome Sciences , University of Washington , 3720 15th Avenue NE , Seattle , Washington 98195 , United States
| | - Brian C Searle
- Department of Genome Sciences , University of Washington , 3720 15th Avenue NE , Seattle , Washington 98195 , United States
| | - Charlie Vaske
- NantOmics , 2919 Mission Street , Santa Cruz , California 95060 , United States
| | - Robert Heaton
- NantOmics , 9600 Medical Center Drive , Rockville , Maryland 20850 , United States
| | - Michael J MacCoss
- Department of Genome Sciences , University of Washington , 3720 15th Avenue NE , Seattle , Washington 98195 , United States
| | - Todd Hembrough
- NantOmics , 9600 Medical Center Drive , Rockville , Maryland 20850 , United States
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334
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Lucas N, Robinson AB, Marcker Espersen M, Mahboob S, Xavier D, Xue J, Balleine RL, deFazio A, Hains PG, Robinson PJ. Accelerated Barocycler Lysis and Extraction Sample Preparation for Clinical Proteomics by Mass Spectrometry. J Proteome Res 2018; 18:399-405. [DOI: 10.1021/acs.jproteome.8b00684] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Natasha Lucas
- ProCan, Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
| | - Andrew B. Robinson
- ProCan, Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
| | - Maiken Marcker Espersen
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW 2145, Australia
| | - Sadia Mahboob
- ProCan, Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
| | - Dylan Xavier
- ProCan, Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
| | - Jing Xue
- Cell Signalling Unit, Children’s Medical Research Institute, The University of Sydney, Westmead, NSW 2145, Australia
| | - Rosemary L. Balleine
- ProCan, Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
| | - Anna deFazio
- Centre for Cancer Research, Westmead Institute for Medical Research, Westmead, NSW 2145, Australia
- Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia
- Department of Gynaecological Oncology, Westmead Hospital, Westmead, NSW 2145, Australia
| | - Peter G. Hains
- ProCan, Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
- Cell Signalling Unit, Children’s Medical Research Institute, The University of Sydney, Westmead, NSW 2145, Australia
| | - Phillip J. Robinson
- ProCan, Children’s Medical Research Institute, Faculty of Medicine and Health, University of Sydney, Westmead, NSW 2145, Australia
- Cell Signalling Unit, Children’s Medical Research Institute, The University of Sydney, Westmead, NSW 2145, Australia
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335
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Cominetti O, Núñez Galindo A, Corthésy J, Valsesia A, Irincheeva I, Kussmann M, Saris WHM, Astrup A, McPherson R, Harper ME, Dent R, Hager J, Dayon L. Obesity shows preserved plasma proteome in large independent clinical cohorts. Sci Rep 2018; 8:16981. [PMID: 30451909 PMCID: PMC6242904 DOI: 10.1038/s41598-018-35321-7] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 11/02/2018] [Indexed: 12/21/2022] Open
Abstract
Holistic human proteome maps are expected to complement comprehensive profile assessment of health and disease phenotypes. However, methodologies to analyze proteomes in human tissue or body fluid samples at relevant scale and performance are still limited in clinical research. Their deployment and demonstration in large enough human populations are even sparser. In the present study, we have characterized and compared the plasma proteomes of two large independent cohorts of obese and overweight individuals using shotgun mass spectrometry (MS)-based proteomics. Herein, we showed, in both populations from different continents of about 500 individuals each, the concordance of plasma protein MS measurements in terms of variability, gender-specificity, and age-relationship. Additionally, we replicated several known and new associations between proteins, clinical and molecular variables, such as insulin and glucose concentrations. In conclusion, our MS-based analyses of plasma samples from independent human cohorts proved the practical feasibility and efficiency of a large and unified discovery/replication approach in proteomics, which was also recently coined “rectangular” design.
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Affiliation(s)
- Ornella Cominetti
- Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | | | - John Corthésy
- Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.,Nutrition Analytics, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Armand Valsesia
- Nutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Irina Irincheeva
- Nutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland.,Clinical Trial Unit, University of Bern, Bern, Switzerland
| | - Martin Kussmann
- Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.,The Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Wim H M Saris
- NUTRIM, School for Nutrition, Toxicology and Metabolism, Department of Human Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Arne Astrup
- Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Ruth McPherson
- Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, Canada
| | - Mary-Ellen Harper
- Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada
| | - Robert Dent
- Ottawa Hospital Weight Management Clinic, The Ottawa Hospital, Ottawa, Canada
| | - Jörg Hager
- Nutrition and Metabolic Health, Nestlé Institute of Health Sciences, Lausanne, Switzerland
| | - Loïc Dayon
- Proteomics, Nestlé Institute of Health Sciences, Lausanne, Switzerland.
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336
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Mandad S, Rahman RU, Centeno TP, Vidal RO, Wildhagen H, Rammner B, Keihani S, Opazo F, Urban I, Ischebeck T, Kirli K, Benito E, Fischer A, Yousefi RY, Dennerlein S, Rehling P, Feussner I, Urlaub H, Bonn S, Rizzoli SO, Fornasiero EF. The codon sequences predict protein lifetimes and other parameters of the protein life cycle in the mouse brain. Sci Rep 2018; 8:16913. [PMID: 30443017 PMCID: PMC6237891 DOI: 10.1038/s41598-018-35277-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 11/02/2018] [Indexed: 12/14/2022] Open
Abstract
The homeostasis of the proteome depends on the tight regulation of the mRNA and protein abundances, of the translation rates, and of the protein lifetimes. Results from several studies on prokaryotes or eukaryotic cell cultures have suggested that protein homeostasis is connected to, and perhaps regulated by, the protein and the codon sequences. However, this has been little investigated for mammals in vivo. Moreover, the link between the coding sequences and one critical parameter, the protein lifetime, has remained largely unexplored, both in vivo and in vitro. We tested this in the mouse brain, and found that the percentages of amino acids and codons in the sequences could predict all of the homeostasis parameters with a precision approaching experimental measurements. A key predictive element was the wobble nucleotide. G-/C-ending codons correlated with higher protein lifetimes, protein abundances, mRNA abundances and translation rates than A-/U-ending codons. Modifying the proportions of G-/C-ending codons could tune these parameters in cell cultures, in a proof-of-principle experiment. We suggest that the coding sequences are strongly linked to protein homeostasis in vivo, albeit it still remains to be determined whether this relation is causal in nature.
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Affiliation(s)
- Sunit Mandad
- Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, Cluster of Excellence Nanoscale Microscopy and Molecular Physiology of the Brain, 37073, Göttingen, Germany
- Bioanalytical Mass Spectrometry Group, Max Planck Institute of Biophysical Chemistry, 37077, Göttingen, Germany
| | - Raza-Ur Rahman
- Laboratory of Computational Systems Biology, German Center for Neurodegenerative Diseases (DZNE), 37075, Göttingen, Germany
- Institute of Medical Systems Biology, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), 20246, Hamburg, Germany
| | - Tonatiuh Pena Centeno
- Laboratory of Computational Systems Biology, German Center for Neurodegenerative Diseases (DZNE), 37075, Göttingen, Germany
| | - Ramon O Vidal
- Laboratory of Computational Systems Biology, German Center for Neurodegenerative Diseases (DZNE), 37075, Göttingen, Germany
| | - Hanna Wildhagen
- Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, Cluster of Excellence Nanoscale Microscopy and Molecular Physiology of the Brain, 37073, Göttingen, Germany
| | - Burkhard Rammner
- Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, Cluster of Excellence Nanoscale Microscopy and Molecular Physiology of the Brain, 37073, Göttingen, Germany
| | - Sarva Keihani
- Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, Cluster of Excellence Nanoscale Microscopy and Molecular Physiology of the Brain, 37073, Göttingen, Germany
| | - Felipe Opazo
- Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, Cluster of Excellence Nanoscale Microscopy and Molecular Physiology of the Brain, 37073, Göttingen, Germany
| | - Inga Urban
- Genes and Behavior Department, Max Planck Institute of Biophysical Chemistry, 37073, Göttingen, Germany
| | - Till Ischebeck
- Department of Plant Biochemistry, Albrecht-von-Haller-Institute, Georg-August-University, 37073, Göttingen, Germany
| | - Koray Kirli
- Department of Cellular Logistics, Max Planck Institute for Biophysical Chemistry, 37073, Göttingen, Germany
| | - Eva Benito
- Laboratory of Epigenetics in Neurodegenerative Diseases, German Center for Neurodegenerative Diseases (DZNE), 37075, Göttingen, Germany
| | - André Fischer
- Laboratory of Epigenetics in Neurodegenerative Diseases, German Center for Neurodegenerative Diseases (DZNE), 37075, Göttingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Roya Y Yousefi
- Department of Cellular Biochemistry, University Medical Center Göttingen, Göttingen, 37073, Germany
| | - Sven Dennerlein
- Department of Cellular Biochemistry, University Medical Center Göttingen, Göttingen, 37073, Germany
| | - Peter Rehling
- Department of Cellular Biochemistry, University Medical Center Göttingen, Göttingen, 37073, Germany
- Max Planck Institute for Biophysical Chemistry, 37073, Göttingen, Germany
| | - Ivo Feussner
- Department of Plant Biochemistry, Albrecht-von-Haller-Institute, Georg-August-University, 37073, Göttingen, Germany
| | - Henning Urlaub
- Department of Clinical Chemistry, University Medical Center Göttingen, 37077, Göttingen, Germany
- Bioanalytical Mass Spectrometry Group, Max Planck Institute of Biophysical Chemistry, 37077, Göttingen, Germany
| | - Stefan Bonn
- Laboratory of Computational Systems Biology, German Center for Neurodegenerative Diseases (DZNE), 37075, Göttingen, Germany.
- Institute of Medical Systems Biology, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), 20246, Hamburg, Germany.
- German Center for Neurodegenerative Diseases (DZNE), 72076, Tübingen, Germany.
| | - Silvio O Rizzoli
- Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, Cluster of Excellence Nanoscale Microscopy and Molecular Physiology of the Brain, 37073, Göttingen, Germany.
- Center for Biostructural Imaging of Neurodegeneration (BIN), 37075, Göttingen, Germany.
| | - Eugenio F Fornasiero
- Department of Neuro- and Sensory Physiology, University Medical Center Göttingen, Cluster of Excellence Nanoscale Microscopy and Molecular Physiology of the Brain, 37073, Göttingen, Germany.
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337
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Limonier F, Willems S, Waeterloos G, Sneyers M, Dhaenens M, Deforce D. Estimating the Reliability of Low-Abundant Signals and Limited Replicate Measurements through MS2 Peak Area in SWATH. Proteomics 2018; 18:e1800186. [PMID: 30387297 DOI: 10.1002/pmic.201800186] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 09/25/2018] [Indexed: 12/26/2022]
Abstract
Sequential windows acquisition of all theoretical fragment ions mass spectrometry (SWATH-MS) provides large-scale protein quantification with high accuracy and selectivity. Nevertheless, reliable quantification of low-abundant signals in complex samples remains challenging, as recently illustrated in a multicenter benchmark study of different label-free software tools. Here, the SWATH Replicates Analysis 2.0 template from Sciex is used to highlight that the relationship between the MS2 peak area and the variability can be described by a function. This functional relationship appears to be largely insensitive to variation in samples or acquisition conditions, suggesting a device-intrinsic property. By using a power regression, it is shown that the MS2 peak area can be used to predict the quantification repeatability without relying on replicate injections, thus contributing to high-throughput confident quantification of low-abundant signals with SWATH-MS.
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Affiliation(s)
- Franck Limonier
- Sciensano, Juliette Wytsman 14, B-1050 Brussels, Belgium.,Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
| | - Sander Willems
- Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
| | | | - Myriam Sneyers
- Sciensano, Juliette Wytsman 14, B-1050 Brussels, Belgium
| | - Maarten Dhaenens
- Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
| | - Dieter Deforce
- Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgium
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338
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Snyder DT, Szalwinski LJ, Wells JM, Cooks RG. Logical MS/MS scans: a new set of operations for tandem mass spectrometry. Analyst 2018; 143:5438-5452. [PMID: 30311922 DOI: 10.1039/c8an01661e] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
A new set of operations for tandem mass spectrometry in a linear ion trap is described. Logical MS/MS operations categorize compounds in mixtures based on characteristic structural features as revealed by MS/MS behavior recorded in multiple fragmentation pathways. This approach is a conceptual extension of tandem mass spectrometry in which interrogation of the full data domain is performed by simultaneous implementation of precursor and neutral loss scans. This process can be thought of as moving through the 2D MS/MS data domain along multiple scan lines simultaneously, which allows experiments that explore the 2D data domain of MS/MS to be couched in terms of logical operations, AND, NAND (not and), OR (inclusive or), XOR (exclusive or), NOT, etc. Examples of particular logical conditions include all precursor ions that fragment to both of two selected product ions (logical AND), or all precursor ions that do not produce a specified fragment ion (logical NOT). These and other operational modes (TRUE/FALSE, XOR, OR, etc.) complement and extend the existing set of conventional MS/MS scans, namely product scans, precursor scans, and neutral loss scans. We describe the implementation of logical MS/MS scans on a commercial linear ion trap mass spectrometer using simple mixtures of amphetamines and fentanyl analogues and argue their utility for complex mixture analysis.
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Affiliation(s)
- Dalton T Snyder
- Purdue University Department of Chemistry, West Lafayette, IN 47907, USA.
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339
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Lau E, Paik DT, Wu JC. Systems-Wide Approaches in Induced Pluripotent Stem Cell Models. ANNUAL REVIEW OF PATHOLOGY-MECHANISMS OF DISEASE 2018; 14:395-419. [PMID: 30379619 DOI: 10.1146/annurev-pathmechdis-012418-013046] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Human induced pluripotent stem cells (iPSCs) provide a renewable supply of patient-specific and tissue-specific cells for cellular and molecular studies of disease mechanisms. Combined with advances in various omics technologies, iPSC models can be used to profile the expression of genes, transcripts, proteins, and metabolites in relevant tissues. In the past 2 years, large panels of iPSC lines have been derived from hundreds of genetically heterogeneous individuals, further enabling genome-wide mapping to identify coexpression networks and elucidate gene regulatory networks. Here, we review recent developments in omics profiling of various molecular phenotypes and the emergence of human iPSCs as a systems biology model of human diseases.
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Affiliation(s)
- Edward Lau
- Stanford Cardiovascular Institute, and Department of Medicine, Division of Cardiology, Stanford University, Stanford, California 94305, USA;
| | - David T Paik
- Stanford Cardiovascular Institute, and Department of Medicine, Division of Cardiology, Stanford University, Stanford, California 94305, USA;
| | - Joseph C Wu
- Stanford Cardiovascular Institute, and Department of Medicine, Division of Cardiology, Stanford University, Stanford, California 94305, USA; .,Department of Radiology, Stanford University, Stanford, California 94305, USA
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340
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Krasny L, Bland P, Kogata N, Wai P, Howard BA, Natrajan RC, Huang PH. SWATH mass spectrometry as a tool for quantitative profiling of the matrisome. J Proteomics 2018; 189:11-22. [PMID: 29501709 PMCID: PMC6215756 DOI: 10.1016/j.jprot.2018.02.026] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Revised: 02/16/2018] [Accepted: 02/19/2018] [Indexed: 12/16/2022]
Abstract
Proteomic analysis of extracellular matrix (ECM) and ECM-associated proteins, collectively known as the matrisome, is a challenging task due to the inherent complexity and insolubility of these proteins. Here we present sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH MS) as a tool for the quantitative analysis of matrisomal proteins in both non-enriched and ECM enriched tissue without the need for prior fractionation. Utilising a spectral library containing 201 matrisomal proteins, we compared the performance and reproducibility of SWATH MS over conventional data-dependent analysis mass spectrometry (DDA MS) in unfractionated murine lung and liver. SWATH MS conferred a 15-20% increase in reproducible peptide identification across replicate experiments in both tissue types and identified 54% more matrisomal proteins in the liver versus DDA MS. We further use SWATH MS to evaluate the quantitative changes in matrisome content that accompanies ECM enrichment. Our data shows that ECM enrichment led to a systematic increase in core matrisomal proteins but resulted in significant losses in matrisome-associated proteins including the cathepsins and proteins of the S100 family. Our proof-of-principle study demonstrates the utility of SWATH MS as a versatile tool for in-depth characterisation of the matrisome in unfractionated and non-enriched tissues. SIGNIFICANCE: The matrisome is a complex network of extracellular matrix (ECM) and ECM-associated proteins that provides scaffolding function to tissues and plays important roles in the regulation of fundamental cellular processes. However, due to its inherent complexity and insolubility, proteomic studies of the matrisome typically require the application of enrichment workflows prior to MS analysis. Such enrichment strategies often lead to losses in soluble matrisome-associated components. In this study, we present sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH MS) as a tool for the quantitative analysis of matrisomal proteins. We show that SWATH MS provides a more reproducible coverage of the matrisome compared to data-dependent analysis (DDA) MS. We also demonstrate that SWATH MS is capable of accurate quantification of matrisomal proteins without prior ECM enrichment and fractionation, which may simplify sample handling workflows and avoid losses in matrisome-associated proteins commonly linked to ECM enrichment.
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Affiliation(s)
- Lukas Krasny
- Division of Molecular Pathology, The Institute of Cancer Research, London, SW3 6JB, UK
| | - Philip Bland
- The Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK
| | - Naoko Kogata
- The Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK
| | - Patty Wai
- Division of Molecular Pathology, The Institute of Cancer Research, London, SW3 6JB, UK; The Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK
| | - Beatrice A Howard
- The Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK
| | - Rachael C Natrajan
- Division of Molecular Pathology, The Institute of Cancer Research, London, SW3 6JB, UK; The Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK
| | - Paul H Huang
- Division of Molecular Pathology, The Institute of Cancer Research, London, SW3 6JB, UK.
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341
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Braccia C, Tomati V, Caci E, Pedemonte N, Armirotti A. SWATH label-free proteomics for cystic fibrosis research. J Cyst Fibros 2018; 18:501-506. [PMID: 30348611 DOI: 10.1016/j.jcf.2018.10.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 10/05/2018] [Accepted: 10/09/2018] [Indexed: 01/05/2023]
Abstract
BACKGROUND Label-free proteomics is a powerful tool for biological investigation. The SWATH protocol, relying on the Pan Human ion library, currently represents the state-of-the-art methodology for this kind of analysis. We recently discovered that this tool is not perfectly suitable for proteomics research in the CF field, as it lacks assays for several proteins crucial for the CF biology, including CFTR. METHODS We extensively investigated the proteome of a very popular model for in vitro research on CF, CFBE41o-, and we used the corresponding data to improve the power of SWATH proteomics for CF investigation. We then used this improved tool to explore in depth the proteome of primary bronchial epithelial (BE) cells deriving from four CF individuals compared with that of four corresponding non-CF controls. By means of advanced bioinformatics tools, we outlined the presence of a number of protein networks being significantly altered by CF. RESULTS Our analysis on patients' BE cells identified 154 proteins dysregulated by the CF pathology (94 upregulated and 60 downregulated). Some known CFTR interactors are present among them, but our analysis also revealed the alteration of other proteins not previously known to be related with CF. CONCLUSIONS The present work outlines the power of SWATH label free proteomics applied to CF research.
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Affiliation(s)
- Clarissa Braccia
- D3Pharmachemistry, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; Dipartimento di Chimica, Università degli Studi di Genova, Via Dodecaneso 31, 16146 Genova, Italy
| | - Valeria Tomati
- U.O.C. Genetica Medica, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147 Genova, Italy
| | - Emanuela Caci
- U.O.C. Genetica Medica, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147 Genova, Italy
| | - Nicoletta Pedemonte
- U.O.C. Genetica Medica, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147 Genova, Italy
| | - Andrea Armirotti
- Analytical Chemistry Lab, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy.
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342
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Chutipongtanate S, Greis KD. Multiplex Biomarker Screening Assay for Urinary Extracellular Vesicles Study: A Targeted Label-Free Proteomic Approach. Sci Rep 2018; 8:15039. [PMID: 30301925 PMCID: PMC6177456 DOI: 10.1038/s41598-018-33280-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 09/26/2018] [Indexed: 12/18/2022] Open
Abstract
The recent advance in targeted label-free proteomics, SWATH-MS, can provide consistent protein detection and reproducible protein quantitation, which is a considerable advantage for biomarker study of urinary extracellular vesicles. We developed a SWATH-MS workflow with a curated spectral library of 1,145 targets. Application of the workflow across nine replicates of three sample types (exosome-like vesicles (ELVs), microvesicles (MVs) and urine proteins (UPs)) resulted in the quantitation of 888 proteins at FDR <1%. The median-coefficient of variation of the 888 proteins in the ELV sample was 7.7%, indicating excellent reproducibility. Data analysis showed common exosome markers, (i.e. CD9, CD63, ALIX, TSG101 and HSP70) were enriched in urinary ELVs as compared to MVs and UPs. The use of a multiplex biomarker screening assay focused on ELVs was investigated, and perspectives in future applications are discussed.
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Affiliation(s)
- Somchai Chutipongtanate
- UC Proteomics Laboratory, Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States.
- Pediatric Translational Research Unit, Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
| | - Kenneth D Greis
- UC Proteomics Laboratory, Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States.
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343
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Kruse R, Højlund K. Proteomic study of skeletal muscle in obesity and type 2 diabetes: progress and potential. Expert Rev Proteomics 2018; 15:817-828. [PMID: 30251560 DOI: 10.1080/14789450.2018.1528147] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Skeletal muscle is the major site of insulin-stimulated glucose uptake and imparts the beneficial effects of exercise, and hence is an important site of insulin resistance in obesity and type 2 diabetes (T2D). Despite extensive molecular biology-oriented research the molecular mechanisms underlying insulin resistance in skeletal muscle remain to be established. Areas covered: The proteomic capabilities have greatly improved over the last decades. This review summarizes the technical challenges in skeletal muscle proteomics studies as well as the results of quantitative proteomic studies of skeletal muscle in relation to obesity, T2D, and exercise. Expert commentary: Current available proteomic studies contribute to the view that insulin resistance in obesity and T2D is associated with increased glycolysis and reduced mitochondrial oxidative metabolism in skeletal muscle, and that the latter can be improved by exercise. Future proteomics studies should be designed to markedly intensify the identification of abnormalities in metabolic and signaling pathways in skeletal muscle of insulin-resistant individuals to increase the understanding of the pathogenesis of T2D, but more importantly to identify multiple novel targets of treatment of which at least some can be safely targeted by novel drugs to treat and prevent T2D and reduce risk of cardiovascular disease.
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Affiliation(s)
- Rikke Kruse
- a The Section of Molecular Diabetes and Metabolism, Department of Clinical Research and Department of Molecular Medicine , University of Southern Denmark , Odense , Denmark.,b Steno Diabetes Center Odense , Odense University Hospital , Odense , Denmark
| | - Kurt Højlund
- a The Section of Molecular Diabetes and Metabolism, Department of Clinical Research and Department of Molecular Medicine , University of Southern Denmark , Odense , Denmark.,b Steno Diabetes Center Odense , Odense University Hospital , Odense , Denmark
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344
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Swiatly A, Plewa S, Matysiak J, Kokot ZJ. Mass spectrometry-based proteomics techniques and their application in ovarian cancer research. J Ovarian Res 2018; 11:88. [PMID: 30270814 PMCID: PMC6166298 DOI: 10.1186/s13048-018-0460-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 09/20/2018] [Indexed: 12/26/2022] Open
Abstract
Ovarian cancer has emerged as one of the leading cause of gynecological malignancies. So far, the measurement of CA125 and HE4 concentrations in blood and transvaginal ultrasound examination are essential ovarian cancer diagnostic methods. However, their sensitivity and specificity are still not sufficient to detect disease at the early stage. Moreover, applied treatment may appear to be ineffective due to drug-resistance. Because of a high mortality rate of ovarian cancer, there is a pressing need to develop innovative strategies leading to a full understanding of complicated molecular pathways related to cancerogenesis. Recent studies have shown the great potential of clinical proteomics in the characterization of many diseases, including ovarian cancer. Therefore, in this review, we summarized achievements of proteomics in ovarian cancer management. Since the development of mass spectrometry has caused a breakthrough in systems biology, we decided to focus on studies based on this technique. According to PubMed engine, in the years 2008-2010 the number of studies concerning OC proteomics was increasing, and since 2010 it has reached a plateau. Proteomics as a rapidly evolving branch of science may be essential in novel biomarkers discovery, therapy decisions, progression predication, monitoring of drug response or resistance. Despite the fact that proteomics has many to offer, we also discussed some limitations occur in ovarian cancer studies. Main difficulties concern both complexity and heterogeneity of ovarian cancer and drawbacks of the mass spectrometry strategies. This review summarizes challenges, capabilities, and promises of the mass spectrometry-based proteomics techniques in ovarian cancer management.
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Affiliation(s)
- Agata Swiatly
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780 Poznań, Poland
| | - Szymon Plewa
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780 Poznań, Poland
| | - Jan Matysiak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780 Poznań, Poland
| | - Zenon J. Kokot
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, Grunwaldzka 6 Street, 60-780 Poznań, Poland
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345
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Banerjee SL, Dionne U, Lambert JP, Bisson N. Targeted proteomics analyses of phosphorylation-dependent signalling networks. J Proteomics 2018; 189:39-47. [DOI: 10.1016/j.jprot.2018.02.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Revised: 01/19/2018] [Accepted: 02/01/2018] [Indexed: 01/18/2023]
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346
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Lin H, He QY, Shi L, Sleeman M, Baker MS, Nice EC. Proteomics and the microbiome: pitfalls and potential. Expert Rev Proteomics 2018; 16:501-511. [PMID: 30223687 DOI: 10.1080/14789450.2018.1523724] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Introduction: Human symbiotic microbiota are now known to play important roles in human health and disease. Significant progress in our understanding of the human microbiome has been driven by recent technological advances in the fields of genomics, transcriptomics, and proteomics. As a complementary method to metagenomics, proteomics is enabling detailed protein profiling of the microbiome to decipher its structure and function and to analyze its relationship with the human body. Fecal proteomics is being increasingly applied to discover and validate potential health and disease biomarkers, and Therapeutic Goods Administration (TGA)-approved instrumentation and a range of clinical assays are being developed that will collectively play key roles in advancing personalized medicine. Areas covered: This review will introduce the complexity of the microbiome and its role in health and disease (in particular the gastrointestinal tract or gut microbiome), discuss current genomic and proteomic methods for studying this system, including the discovery of potential biomarkers, and outline the development of clinically accepted protocols leading to personalized medicine. Expert commentary: Recognition of the important role the microbiome plays in both health and disease is driving current research in this key area. A proteogenomics approach will be essential to unravel the biologies underlying this complex network.
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Affiliation(s)
- Huafeng Lin
- a Department of Biotechnology , College of Life Science and Technology, Jinan University , Guangzhou , Guangdong , China.,b Institute of Food Safety and Nutrition Research , Jinan University , Guangzhou , China
| | - Qing-Yu He
- c Institute of Life and Health Engineering, College of Life Science and Technology , Jinan University , Guangzhou , China
| | - Lei Shi
- b Institute of Food Safety and Nutrition Research , Jinan University , Guangzhou , China
| | - Mark Sleeman
- d Biomedicine Discovery Institute , Monash University , Melbourne , Australia
| | - Mark S Baker
- e Department of Biomedical Sciences, Faculty of Medicine and Health Sciences , Macquarie University , Sydney , Australia
| | - Edouard C Nice
- f Department of Biochemistry and Molecular Biology , Monash University , Melbourne , Victoria , Australia
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347
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Ludwig C, Gillet L, Rosenberger G, Amon S, Collins BC, Aebersold R. Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial. Mol Syst Biol 2018; 14:e8126. [PMID: 30104418 PMCID: PMC6088389 DOI: 10.15252/msb.20178126] [Citation(s) in RCA: 625] [Impact Index Per Article: 104.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Revised: 05/11/2018] [Accepted: 05/15/2018] [Indexed: 01/16/2023] Open
Abstract
Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.
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Affiliation(s)
- Christina Ludwig
- Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich (TUM), Freising, Germany
| | - Ludovic Gillet
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - George Rosenberger
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Sabine Amon
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Ben C Collins
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- Faculty of Science, University of Zurich, Zurich, Switzerland
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348
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Haynes SE, Majmudar JD, Martin BR. DIA-SIFT: A Precursor and Product Ion Filter for Accurate Stable Isotope Data-Independent Acquisition Proteomics. Anal Chem 2018; 90:8722-8726. [PMID: 29989796 DOI: 10.1021/acs.analchem.8b01618] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Quantitative mass spectrometry-based protein profiling is widely used to measure protein levels across different treatments or disease states, yet current mass spectrometry acquisition methods present distinct limitations. While data-independent acquisition (DIA) bypasses the stochastic nature of data-dependent acquisition (DDA), fragment spectra derived from DIA are often complex and challenging to deconvolve. In-line ion mobility separation (IMS) adds an additional dimension to increase peak capacity for more efficient product ion assignment. As a similar strategy to sequential window acquisition methods (SWATH), IMS-enabled DIA methods rival DDA methods for protein annotation. Here we evaluate IMS-DIA quantitative accuracy using stable isotope labeling by amino acids in cell culture (SILAC). Since SILAC analysis doubles the sample complexity, we find that IMS-DIA analysis is not sufficiently accurate for sensitive quantitation. However, SILAC precursor pairs share common retention and drift times, and both species cofragment to yield multiple quantifiable isotopic y-ion peak pairs. Since y-ion SILAC ratios are intrinsic for each quantified precursor, combined MS1 and y-ion ratio analysis significantly increases the total number of measurements. With increased sampling, we present DIA-SIFT ( SILAC Intrinsic Filtering Tool), a simple statistical algorithm to identify and eliminate poorly quantified MS1 and/or MS2 events. DIA-SIFT combines both MS1 and y-ion ratios, removes outliers, and provides more accurate and precise quantitation (<15% CV) without removing any proteins from the final analysis. Overall, pooled MS1 and MS2 quantitation increases sampling in IMS-DIA SILAC analyses for accurate and precise quantitation.
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Affiliation(s)
- Sarah E Haynes
- Department of Chemistry , University of Michigan , 930 N. University Avenue, Ann Arbor , Michigan 48109 , United States
| | - Jaimeen D Majmudar
- Department of Chemistry , University of Michigan , 930 N. University Avenue, Ann Arbor , Michigan 48109 , United States
| | - Brent R Martin
- Department of Chemistry , University of Michigan , 930 N. University Avenue, Ann Arbor , Michigan 48109 , United States
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349
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Hakobyan A, Liesack W, Glatter T. Crude-MS Strategy for in-Depth Proteome Analysis of the Methane-Oxidizing Methylocystis sp. strain SC2. J Proteome Res 2018; 17:3086-3103. [DOI: 10.1021/acs.jproteome.8b00216] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
| | - Werner Liesack
- Center for Synthetic Microbiology (SYNMIKRO), Philipps-Universität Marburg, Karl-von-Frisch-Str. 16, D-35043 Marburg, Germany
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350
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Piekos SC, Chen L, Wang P, Shi J, Yaqoob S, Zhu HJ, Ma X, Zhong XB. Consequences of Phenytoin Exposure on Hepatic Cytochrome P450 Expression during Postnatal Liver Maturation in Mice. Drug Metab Dispos 2018; 46:1241-1250. [PMID: 29884652 DOI: 10.1124/dmd.118.080861] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 06/01/2018] [Indexed: 12/15/2022] Open
Abstract
The induction of cytochrome P450 (P450) enzymes in response to drug treatment is a significant contributing factor to drug-drug interactions, which may reduce therapeutic efficacy and/or cause toxicity. Since most studies on P450 induction are performed in adults, enzyme induction at neonatal, infant, and adolescent ages is not well understood. Previous work defined the postnatal ontogeny of drug-metabolizing P450s in human and mouse livers; however, there are limited data on the ontogeny of the induction potential of each enzyme in response to drug treatment. Induction of P450s at the neonatal age may also cause permanent alterations in P450 expression in adults. The goal of this study was to investigate the short- and long-term effects of phenytoin treatment on mRNA and protein expressions and enzyme activities of CYP2B10, 2C29, 3A11, and 3A16 at different ages during postnatal liver maturation in mice. Induction of mRNA immediately following phenytoin treatment appeared to depend on basal expression of the enzyme at a specific age. While neonatal mice showed the greatest fold changes in CYP2B10, 2C29, and 3A11 mRNA expression following treatment, the levels of induced protein expression and enzymatic activity were much lower than that of induced levels in adults. The expression of fetal CYP3A16 was repressed by phenytoin treatment. Neonatal treatment with phenytoin did not permanently induce enzyme expression in adulthood. Taken together, our data suggest that inducibility of drug-metabolizing P450s is much lower in neonatal mice than it is in adults and neonatal induction by phenytoin is not permanent.
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Affiliation(s)
- Stephanie C Piekos
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, Connecticut (S.C.P., L.C., S.Y., X.-b.Z.); Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania (P.W., X.M.); and Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan (J.S., H.-J.Z.)
| | - Liming Chen
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, Connecticut (S.C.P., L.C., S.Y., X.-b.Z.); Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania (P.W., X.M.); and Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan (J.S., H.-J.Z.)
| | - Pengcheng Wang
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, Connecticut (S.C.P., L.C., S.Y., X.-b.Z.); Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania (P.W., X.M.); and Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan (J.S., H.-J.Z.)
| | - Jian Shi
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, Connecticut (S.C.P., L.C., S.Y., X.-b.Z.); Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania (P.W., X.M.); and Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan (J.S., H.-J.Z.)
| | - Sharon Yaqoob
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, Connecticut (S.C.P., L.C., S.Y., X.-b.Z.); Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania (P.W., X.M.); and Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan (J.S., H.-J.Z.)
| | - Hao-Jie Zhu
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, Connecticut (S.C.P., L.C., S.Y., X.-b.Z.); Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania (P.W., X.M.); and Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan (J.S., H.-J.Z.)
| | - Xiaochao Ma
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, Connecticut (S.C.P., L.C., S.Y., X.-b.Z.); Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania (P.W., X.M.); and Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan (J.S., H.-J.Z.)
| | - Xiao-Bo Zhong
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, Connecticut (S.C.P., L.C., S.Y., X.-b.Z.); Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania (P.W., X.M.); and Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan (J.S., H.-J.Z.)
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