Literature DB >> 18707148

Precursor-ion mass re-estimation improves peptide identification on hybrid instruments.

Roland Luethy1, Darren E Kessner, Jonathan E Katz, Brendan Maclean, Robert Grothe, Kian Kani, Vitor Faça, Sharon Pitteri, Samir Hanash, David B Agus, Parag Mallick.   

Abstract

Mass spectrometry-based proteomics experiments have become an important tool for studying biological systems. Identifying the proteins in complex mixtures by assigning peptide fragmentation spectra to peptide sequences is an important step in the proteomics process. The 1-2 ppm mass-accuracy of hybrid instruments, like the LTQ-FT, has been cited as a key factor in their ability to identify a larger number of peptides with greater confidence than competing instruments. However, in replicate experiments of an 18-protein mixture, we note parent masses deviate 171 ppm, on average, for ion-trap data directed identifications and 8 ppm, on average, for preview Fourier transform (FT) data directed identifications. These deviations are neither caused by poor calibration nor by excessive ion-loading and are most likely due to errors in parent mass estimation. To improve these deviations, we introduce msPrefix, a program to re-estimate a peptide's parent mass from an associated high-accuracy full-scan survey spectrum. In 18-protein mixture experiments, msPrefix parent mass estimates deviate only 1 ppm, on average, from the identified peptides. In a cell lysate experiment searched with a tolerance of 50 ppm, 2295 peptides were confidently identified using native data and 4560 using msPrefixed data. Likewise, in a plasma experiment searched with a tolerance of 50 ppm, 326 peptides were identified using native data and 1216 using msPrefixed data. msPrefix is also able to determine which MS/MS spectra were possibly derived from multiple precursor ions. In complex mixture experiments, we demonstrate that more than 50% of triggered MS/MS may have had multiple precursor ions and note that spectra with multiple candidate ions are less likely to result in an identification using TANDEM. These results demonstrate integration of msPrefix into traditional shotgun proteomics workflows significantly improves identification results.

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Year:  2008        PMID: 18707148      PMCID: PMC4673049          DOI: 10.1021/pr800307m

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  35 in total

1.  De novo peptide sequencing via tandem mass spectrometry.

Authors:  V Dancík; T A Addona; K R Clauser; J E Vath; P A Pevzner
Journal:  J Comput Biol       Date:  1999 Fall-Winter       Impact factor: 1.479

Review 2.  Proteomics: the first decade and beyond.

Authors:  Scott D Patterson; Ruedi H Aebersold
Journal:  Nat Genet       Date:  2003-03       Impact factor: 38.330

3.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

Authors:  Andrew Keller; Alexey I Nesvizhskii; Eugene Kolker; Ruedi Aebersold
Journal:  Anal Chem       Date:  2002-10-15       Impact factor: 6.986

4.  TANDEM: matching proteins with tandem mass spectra.

Authors:  Robertson Craig; Ronald C Beavis
Journal:  Bioinformatics       Date:  2004-02-19       Impact factor: 6.937

5.  MS2Grouper: group assessment and synthetic replacement of duplicate proteomic tandem mass spectra.

Authors:  David L Tabb; Melissa R Thompson; Gurusahai Khalsa-Moyers; Nathan C VerBerkmoes; W Hayes McDonald
Journal:  J Am Soc Mass Spectrom       Date:  2005-08       Impact factor: 3.109

6.  Peptide sequence tags for fast database search in mass-spectrometry.

Authors:  Ari Frank; Stephen Tanner; Vineet Bafna; Pavel Pevzner
Journal:  J Proteome Res       Date:  2005 Jul-Aug       Impact factor: 4.466

7.  Perspective: a program to improve protein biomarker discovery for cancer.

Authors:  Ruedi Aebersold; Leigh Anderson; Richard Caprioli; Brian Druker; Leland Hartwell; Richard Smith
Journal:  J Proteome Res       Date:  2005 Jul-Aug       Impact factor: 4.466

8.  Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

Authors:  Gilbert S Omenn; David J States; Marcin Adamski; Thomas W Blackwell; Rajasree Menon; Henning Hermjakob; Rolf Apweiler; Brian B Haab; Richard J Simpson; James S Eddes; Eugene A Kapp; Robert L Moritz; Daniel W Chan; Alex J Rai; Arie Admon; Ruedi Aebersold; Jimmy Eng; William S Hancock; Stanley A Hefta; Helmut Meyer; Young-Ki Paik; Jong-Shin Yoo; Peipei Ping; Joel Pounds; Joshua Adkins; Xiaohong Qian; Rong Wang; Valerie Wasinger; Chi Yue Wu; Xiaohang Zhao; Rong Zeng; Alexander Archakov; Akira Tsugita; Ilan Beer; Akhilesh Pandey; Michael Pisano; Philip Andrews; Harald Tammen; David W Speicher; Samir M Hanash
Journal:  Proteomics       Date:  2005-08       Impact factor: 3.984

9.  Determination of monoisotopic masses and ion populations for large biomolecules from resolved isotopic distributions.

Authors:  M W Senko; S C Beu; F W McLaffertycor
Journal:  J Am Soc Mass Spectrom       Date:  1995-04       Impact factor: 3.109

10.  A physical and functional map of the human TNF-alpha/NF-kappa B signal transduction pathway.

Authors:  Tewis Bouwmeester; Angela Bauch; Heinz Ruffner; Pierre-Olivier Angrand; Giovanna Bergamini; Karen Croughton; Cristina Cruciat; Dirk Eberhard; Julien Gagneur; Sonja Ghidelli; Carsten Hopf; Bettina Huhse; Raffaella Mangano; Anne-Marie Michon; Markus Schirle; Judith Schlegl; Markus Schwab; Martin A Stein; Andreas Bauer; Georg Casari; Gerard Drewes; Anne-Claude Gavin; David B Jackson; Gerard Joberty; Gitte Neubauer; Jens Rick; Bernhard Kuster; Giulio Superti-Furga
Journal:  Nat Cell Biol       Date:  2004-01-25       Impact factor: 28.824

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  18 in total

1.  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

Review 2.  Quantitative neuroproteomics: classical and novel tools for studying neural differentiation and function.

Authors:  Luca Colucci-D'Amato; Annarita Farina; Johannes P C Vissers; Angela Chambery
Journal:  Stem Cell Rev Rep       Date:  2011-03       Impact factor: 5.739

Review 3.  Protein analysis by shotgun/bottom-up proteomics.

Authors:  Yaoyang Zhang; Bryan R Fonslow; Bing Shan; Moon-Chang Baek; John R Yates
Journal:  Chem Rev       Date:  2013-02-26       Impact factor: 60.622

4.  MixGF: spectral probabilities for mixture spectra from more than one peptide.

Authors:  Jian Wang; Philip E Bourne; Nuno Bandeira
Journal:  Mol Cell Proteomics       Date:  2014-09-15       Impact factor: 5.911

Review 5.  A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics.

Authors:  Alexey I Nesvizhskii
Journal:  J Proteomics       Date:  2010-09-08       Impact factor: 4.044

6.  Integrated post-experiment monoisotopic mass refinement: an integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

Authors:  Hee-Jung Jung; Samuel O Purvine; Hokeun Kim; Vladislav A Petyuk; Seok-Won Hyung; Matthew E Monroe; Dong-Gi Mun; Kyong-Chul Kim; Jong-Moon Park; Su-Jin Kim; Nikola Tolic; Gordon W Slysz; Ronald J Moore; Rui Zhao; Joshua N Adkins; Gordon A Anderson; Hookeun Lee; David G Camp; Myeong-Hee Yu; Richard D Smith; Sang-Won Lee
Journal:  Anal Chem       Date:  2010-10-15       Impact factor: 6.986

7.  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

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

Authors:  Inamul Hasan Madar; Seung-Ik Ko; Hokeun Kim; Dong-Gi Mun; Sangtae Kim; Richard D Smith; Sang-Won Lee
Journal:  Anal Chem       Date:  2016-12-22       Impact factor: 6.986

9.  Comprehensive absolute quantification of the cytosolic proteome of Bacillus subtilis by data independent, parallel fragmentation in liquid chromatography/mass spectrometry (LC/MS(E)).

Authors:  Jan Muntel; Vincent Fromion; Anne Goelzer; Sandra Maaβ; Ulrike Mäder; Knut Büttner; Michael Hecker; Dörte Becher
Journal:  Mol Cell Proteomics       Date:  2014-01-31       Impact factor: 5.911

10.  Post analysis data acquisition for the iterative MS/MS sampling of proteomics mixtures.

Authors:  Michael R Hoopmann; Gennifer E Merrihew; Priska D von Haller; Michael J MacCoss
Journal:  J Proteome Res       Date:  2009-04       Impact factor: 4.466

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