Literature DB >> 21683145

The importance of the digest: proteolysis and absolute quantification in proteomics.

Philip Brownridge1, Robert J Beynon.   

Abstract

Virtually all mass spectrometric-based methods for quantitative proteomics are at the peptide level, whether label-mediated or label-free. Absolute quantification in particular is based on the measurement of limit peptides, defined as those peptides that cannot be further fragmented by the protease in use. Complete release of analyte and (stable isotope labelled) standard ensures that the most reliable quantification data are recovered, especially when the standard peptides are in a different primary sequence context, such as sometimes occurs in the QconCAT methodology. Moreover, in label-free methods, incomplete digestion would diminish the ion current attributable to limit peptides and lead to artifactually low quantification data. It follows that an essential requirement for peptide-based absolute quantification in proteomics is complete and consistent proteolysis to limit peptides. In this paper we describe strategies to assess completeness of proteolysis and discuss the potential for variance in digestion efficiency to compromise the ensuing quantification data. We examine the potential for kinetically favoured routes of proteolysis, particularly at the last stages of the digestion, to direct products into 'dead-end' mis-cleaved products.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21683145     DOI: 10.1016/j.ymeth.2011.05.005

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  35 in total

1.  Absolute quantification of the glycolytic pathway in yeast: deployment of a complete QconCAT approach.

Authors:  Kathleen M Carroll; Deborah M Simpson; Claire E Eyers; Christopher G Knight; Philip Brownridge; Warwick B Dunn; Catherine L Winder; Karin Lanthaler; Pinar Pir; Naglis Malys; Douglas B Kell; Stephen G Oliver; Simon J Gaskell; Robert J Beynon
Journal:  Mol Cell Proteomics       Date:  2011-09-19       Impact factor: 5.911

2.  Multiple Reaction Monitoring Enables Precise Quantification of 97 Proteins in Dried Blood Spots.

Authors:  Andrew G Chambers; Andrew J Percy; Juncong Yang; Christoph H Borchers
Journal:  Mol Cell Proteomics       Date:  2015-09-04       Impact factor: 5.911

3.  Peptide production and decay rates affect the quantitative accuracy of protein cleavage isotope dilution mass spectrometry (PC-IDMS).

Authors:  Christopher M Shuford; Ronald R Sederoff; Vincent L Chiang; David C Muddiman
Journal:  Mol Cell Proteomics       Date:  2012-05-17       Impact factor: 5.911

4.  Quantitative Mass Spectrometry-Based Proteomics: An Overview.

Authors:  Svitlana Rozanova; Katalin Barkovits; Miroslav Nikolov; Carla Schmidt; Henning Urlaub; Katrin Marcus
Journal:  Methods Mol Biol       Date:  2021

5.  Prediction of missed proteolytic cleavages for the selection of surrogate peptides for quantitative proteomics.

Authors:  Craig Lawless; Simon J Hubbard
Journal:  OMICS       Date:  2012-07-17

6.  Quantitation of the dynamic profiles of the innate immune response using multiplex selected reaction monitoring-mass spectrometry.

Authors:  Yingxin Zhao; Bing Tian; Chukwudi B Edeh; Allan R Brasier
Journal:  Mol Cell Proteomics       Date:  2013-02-15       Impact factor: 5.911

7.  Absolute quantification of transcription factors during cellular differentiation using multiplexed targeted proteomics.

Authors:  Jovan Simicevic; Adrien W Schmid; Paola A Gilardoni; Benjamin Zoller; Sunil K Raghav; Irina Krier; Carine Gubelmann; Frédérique Lisacek; Felix Naef; Marc Moniatte; Bart Deplancke
Journal:  Nat Methods       Date:  2013-04-14       Impact factor: 28.547

8.  IQcat: multiplexed protein quantification by isoelectric QconCAT.

Authors:  Ryan J Austin; Deborah K Chang; Carly A Holstein; Lik W Lee; Jenni Risler; Jonathan H Wang; Lee Adams; Nicolle B Krusberski; Daniel B Martin
Journal:  Proteomics       Date:  2012-06-19       Impact factor: 3.984

9.  Comprehensive analysis of protein digestion using six trypsins reveals the origin of trypsin as a significant source of variability in proteomics.

Authors:  Scott J Walmsley; Paul A Rudnick; Yuxue Liang; Qian Dong; Stephen E Stein; Alexey I Nesvizhskii
Journal:  J Proteome Res       Date:  2013-11-14       Impact factor: 4.466

10.  Label-free quantification in ion mobility-enhanced data-independent acquisition proteomics.

Authors:  Ute Distler; Jörg Kuharev; Pedro Navarro; Stefan Tenzer
Journal:  Nat Protoc       Date:  2016-03-24       Impact factor: 13.491

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