Literature DB >> 26217018

Peptide-Centric Proteome Analysis: An Alternative Strategy for the Analysis of Tandem Mass Spectrometry Data.

Ying S Ting1, Jarrett D Egertson1, Samuel H Payne2, Sangtae Kim2, Brendan MacLean1, Lukas Käll3, Ruedi Aebersold4, Richard D Smith2, William Stafford Noble5, Michael J MacCoss6.   

Abstract

In mass spectrometry-based bottom-up proteomics, data-independent acquisition is an emerging technique because of its comprehensive and unbiased sampling of precursor ions. However, current data-independent acquisition methods use wide precursor isolation windows, resulting in cofragmentation and complex mixture spectra. Thus, conventional database searching tools that identify peptides by interpreting individual tandem MS spectra are inherently limited in analyzing data-independent acquisition data. Here we discuss an alternative approach, peptide-centric analysis, which tests directly for the presence and absence of query peptides. We discuss how peptide-centric analysis resolves some limitations of traditional spectrum-centric analysis, and we outline the unique characteristics of peptide-centric analysis in general.
© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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Year:  2015        PMID: 26217018      PMCID: PMC4563716          DOI: 10.1074/mcp.O114.047035

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  55 in total

1.  XDIA: improving on the label-free data-independent analysis.

Authors:  Paulo C Carvalho; Xuemei Han; Tao Xu; Daniel Cociorva; Maria da Gloria Carvalho; Valmir C Barbosa; John R Yates
Journal:  Bioinformatics       Date:  2010-01-26       Impact factor: 6.937

2.  mProphet: automated data processing and statistical validation for large-scale SRM experiments.

Authors:  Lukas Reiter; Oliver Rinner; Paola Picotti; Ruth Hüttenhain; Martin Beck; Mi-Youn Brusniak; Michael O Hengartner; Ruedi Aebersold
Journal:  Nat Methods       Date:  2011-03-20       Impact factor: 28.547

3.  More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS.

Authors:  Annette Michalski; Juergen Cox; Matthias Mann
Journal:  J Proteome Res       Date:  2011-02-28       Impact factor: 4.466

4.  Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

Authors:  Brendan MacLean; Daniela M Tomazela; Nicholas Shulman; Matthew Chambers; Gregory L Finney; Barbara Frewen; Randall Kern; David L Tabb; Daniel C Liebler; Michael J MacCoss
Journal:  Bioinformatics       Date:  2010-02-09       Impact factor: 6.937

5.  Peptide identification by database search of mixture tandem mass spectra.

Authors:  Jian Wang; Philip E Bourne; Nuno Bandeira
Journal:  Mol Cell Proteomics       Date:  2011-08-23       Impact factor: 5.911

6.  Quantifying the impact of chimera MS/MS spectra on peptide identification in large-scale proteomics studies.

Authors:  Stephane Houel; Robert Abernathy; Kutralanathan Renganathan; Karen Meyer-Arendt; Natalie G Ahn; William M Old
Journal:  J Proteome Res       Date:  2010-08-06       Impact factor: 4.466

7.  DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics.

Authors:  Chih-Chiang Tsou; Dmitry Avtonomov; Brett Larsen; Monika Tucholska; Hyungwon Choi; Anne-Claude Gingras; Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2015-01-19       Impact factor: 28.547

8.  The importance of peptide detectability for protein identification, quantification, and experiment design in MS/MS proteomics.

Authors:  Yong Fuga Li; Randy J Arnold; Haixu Tang; Predrag Radivojac
Journal:  J Proteome Res       Date:  2010-11-10       Impact factor: 4.466

9.  Comparison of database search strategies for high precursor mass accuracy MS/MS data.

Authors:  Edward J Hsieh; Michael R Hoopmann; Brendan MacLean; Michael J MacCoss
Journal:  J Proteome Res       Date:  2010-02-05       Impact factor: 4.466

10.  Spectrum-to-spectrum searching using a proteome-wide spectral library.

Authors:  Chia-Yu Yen; Stephane Houel; Natalie G Ahn; William M Old
Journal:  Mol Cell Proteomics       Date:  2011-04-30       Impact factor: 5.911

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  43 in total

1.  DeMix-Q: Quantification-Centered Data Processing Workflow.

Authors:  Bo Zhang; Lukas Käll; Roman A Zubarev
Journal:  Mol Cell Proteomics       Date:  2016-01-04       Impact factor: 5.911

2.  Relative protein quantification and accessible biology in lung tumor proteomes from four LC-MS/MS discovery platforms.

Authors:  Paul A Stewart; Bin Fang; Robbert J C Slebos; Guolin Zhang; Adam L Borne; Katherine Fellows; Jamie K Teer; Y Ann Chen; Eric Welsh; Steven A Eschrich; Eric B Haura; John M Koomen
Journal:  Proteomics       Date:  2017-03       Impact factor: 3.984

3.  Site-specific analysis of changes in the glycosylation of proteins in liver cirrhosis using data-independent workflow with soft fragmentation.

Authors:  Miloslav Sanda; Lihua Zhang; Nathan J Edwards; Radoslav Goldman
Journal:  Anal Bioanal Chem       Date:  2016-11-07       Impact factor: 4.142

4.  Application of SWATH Proteomics to Mouse Biology.

Authors:  Yibo Wu; Evan G Williams; Ruedi Aebersold
Journal:  Curr Protoc Mouse Biol       Date:  2017-06-19

Review 5.  The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics.

Authors:  Lindsay K Pino; Brian C Searle; James G Bollinger; Brook Nunn; Brendan MacLean; Michael J MacCoss
Journal:  Mass Spectrom Rev       Date:  2017-07-09       Impact factor: 10.946

6.  Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries.

Authors:  Lindsay K Pino; Seth C Just; Michael J MacCoss; Brian C Searle
Journal:  Mol Cell Proteomics       Date:  2020-04-20       Impact factor: 5.911

7.  SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles.

Authors:  George Rosenberger; Moritz Heusel; Isabell Bludau; Ben C Collins; Claudia Martelli; Evan G Williams; Peng Xue; Yansheng Liu; Ruedi Aebersold; Andrea Califano
Journal:  Cell Syst       Date:  2020-12-16       Impact factor: 10.304

8.  An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts.

Authors:  Xiaomeng Shen; Shichen Shen; Jun Li; Qiang Hu; Lei Nie; Chengjian Tu; Xue Wang; Benjamin Orsburn; Jianmin Wang; Jun Qu
Journal:  J Proteome Res       Date:  2017-05-25       Impact factor: 4.466

Review 9.  Clinical applications of quantitative proteomics using targeted and untargeted data-independent acquisition techniques.

Authors:  Jesse G Meyer; Birgit Schilling
Journal:  Expert Rev Proteomics       Date:  2017-05       Impact factor: 3.940

10.  Improving mitochondrial function with SS-31 reverses age-related redox stress and improves exercise tolerance in aged mice.

Authors:  Matthew D Campbell; Jicheng Duan; Ashton T Samuelson; Matthew J Gaffrey; Gennifer E Merrihew; Jarrett D Egertson; Lu Wang; Theo K Bammler; Ronald J Moore; Collin C White; Terrance J Kavanagh; Joachim G Voss; Hazel H Szeto; Peter S Rabinovitch; Michael J MacCoss; Wei-Jun Qian; David J Marcinek
Journal:  Free Radic Biol Med       Date:  2018-12-28       Impact factor: 7.376

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