Literature DB >> 27966901

Multiplexed Post-Experimental Monoisotopic Mass Refinement (mPE-MMR) to Increase Sensitivity and Accuracy in Peptide Identifications from Tandem Mass Spectra of Cofragmentation.

Inamul Hasan Madar1, Seung-Ik Ko1, Hokeun Kim1, Dong-Gi Mun1, Sangtae Kim2, Richard D Smith2, Sang-Won Lee1.   

Abstract

Mass spectrometry (MS)-based proteomics, which uses high-resolution hybrid mass spectrometers such as the quadrupole-orbitrap mass spectrometer, can yield tens of thousands of tandem mass (MS/MS) spectra of high resolution during a routine bottom-up experiment. Despite being a fundamental and key step in MS-based proteomics, the accurate determination and assignment of precursor monoisotopic masses to the MS/MS spectra remains difficult. The difficulties stem from imperfect isotopic envelopes of precursor ions, inaccurate charge states for precursor ions, and cofragmentation. We describe a composite method of utilizing MS data to assign accurate monoisotopic masses to MS/MS spectra, including those subject to cofragmentation. The method, "multiplexed post-experiment monoisotopic mass refinement" (mPE-MMR), consists of the following: multiplexing of precursor masses to assign multiple monoisotopic masses of cofragmented peptides to the corresponding multiplexed MS/MS spectra, multiplexing of charge states to assign correct charges to the precursor ions of MS/MS spectra with no charge information, and mass correction for inaccurate monoisotopic peak picking. When combined with MS-GF+, a database search algorithm based on fragment mass difference, mPE-MMR effectively increases both sensitivity and accuracy in peptide identification from complex high-throughput proteomics data compared to conventional methods.

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Year:  2016        PMID: 27966901      PMCID: PMC5627999          DOI: 10.1021/acs.analchem.6b03874

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  32 in total

1.  Increasing information from shotgun proteomic data by accounting for misassigned precursor ion masses.

Authors:  Alexander Scherl; Yihsuan Shannon Tsai; Scott A Shaffer; David R Goodlett
Journal:  Proteomics       Date:  2008-07       Impact factor: 3.984

2.  Isotopic peak intensity ratio based algorithm for determination of isotopic clusters and monoisotopic masses of polypeptides from high-resolution mass spectrometric data.

Authors:  Kunsoo Park; Joo Young Yoon; Sunho Lee; Eunok Paek; Heejin Park; Hee-Jung Jung; Sang-Won Lee
Journal:  Anal Chem       Date:  2008-08-28       Impact factor: 6.986

3.  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

4.  MaxQuant for in-depth analysis of large SILAC datasets.

Authors:  Stefka Tyanova; Matthias Mann; Jürgen Cox
Journal:  Methods Mol Biol       Date:  2014

5.  Estimating influence of cofragmentation on peptide quantification and identification in iTRAQ experiments by simulating multiplexed spectra.

Authors:  Honglan Li; Kyu-Baek Hwang; Dong-Gi Mun; Hokeun Kim; Hangyeore Lee; Sang-Won Lee; Eunok Paek
Journal:  J Proteome Res       Date:  2014-06-23       Impact factor: 4.466

6.  Computing exact p-values for a cross-correlation shotgun proteomics score function.

Authors:  J Jeffry Howbert; William Stafford Noble
Journal:  Mol Cell Proteomics       Date:  2014-06-02       Impact factor: 5.911

7.  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

8.  Charge prediction machine: tool for inferring precursor charge states of electron transfer dissociation tandem mass spectra.

Authors:  Paulo C Carvalho; Daniel Cociorva; Catherine C L Wong; Maria da Gloria da C Carvalho; Valmir C Barbosa; John R Yates
Journal:  Anal Chem       Date:  2009-03-01       Impact factor: 6.986

9.  A cross-platform toolkit for mass spectrometry and proteomics.

Authors:  Matthew C Chambers; Brendan Maclean; Robert Burke; Dario Amodei; Daniel L Ruderman; Steffen Neumann; Laurent Gatto; Bernd Fischer; Brian Pratt; Jarrett Egertson; Katherine Hoff; Darren Kessner; Natalie Tasman; Nicholas Shulman; Barbara Frewen; Tahmina A Baker; Mi-Youn Brusniak; Christopher Paulse; David Creasy; Lisa Flashner; Kian Kani; Chris Moulding; Sean L Seymour; Lydia M Nuwaysir; Brent Lefebvre; Frank Kuhlmann; Joe Roark; Paape Rainer; Suckau Detlev; Tina Hemenway; Andreas Huhmer; James Langridge; Brian Connolly; Trey Chadick; Krisztina Holly; Josh Eckels; Eric W Deutsch; Robert L Moritz; Jonathan E Katz; David B Agus; Michael MacCoss; David L Tabb; Parag Mallick
Journal:  Nat Biotechnol       Date:  2012-10       Impact factor: 54.908

10.  MS-GF+ makes progress towards a universal database search tool for proteomics.

Authors:  Sangtae Kim; Pavel A Pevzner
Journal:  Nat Commun       Date:  2014-10-31       Impact factor: 14.919

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  2 in total

1.  Comprehensive identification of peptides in tandem mass spectra using an efficient open search engine.

Authors:  Hao Chi; Chao Liu; Hao Yang; Wen-Feng Zeng; Long Wu; Wen-Jing Zhou; Rui-Min Wang; Xiu-Nan Niu; Yue-He Ding; Yao Zhang; Zhao-Wei Wang; Zhen-Lin Chen; Rui-Xiang Sun; Tao Liu; Guang-Ming Tan; Meng-Qiu Dong; Ping Xu; Pei-Heng Zhang; Si-Min He
Journal:  Nat Biotechnol       Date:  2018-10-08       Impact factor: 54.908

2.  Full-Featured, Real-Time Database Searching Platform Enables Fast and Accurate Multiplexed Quantitative Proteomics.

Authors:  Devin K Schweppe; Jimmy K Eng; Qing Yu; Derek Bailey; Ramin Rad; Jose Navarrete-Perea; Edward L Huttlin; Brian K Erickson; Joao A Paulo; Steven P Gygi
Journal:  J Proteome Res       Date:  2020-04-06       Impact factor: 4.466

  2 in total

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