Literature DB >> 23768245

Measuring and managing ratio compression for accurate iTRAQ/TMT quantification.

Mikhail M Savitski1, Toby Mathieson, Nico Zinn, Gavain Sweetman, Carola Doce, Isabelle Becher, Fiona Pachl, Bernhard Kuster, Marcus Bantscheff.   

Abstract

Isobaric mass tagging (e.g., TMT and iTRAQ) is a precise and sensitive multiplexed peptide/protein quantification technique in mass spectrometry. However, accurate quantification of complex proteomic samples is impaired by cofragmentation of peptides, leading to systematic underestimation of quantitative ratios. Label-free quantification strategies do not suffer from such an accuracy bias but cannot be multiplexed and are less precise. Here, we compared protein quantification results obtained with these methods for a chemoproteomic competition binding experiment and evaluated the utility of measures of spectrum purity in survey spectra for estimating the impact of cofragmentation on measured TMT-ratios. While applying stringent interference filters enables substantially more accurate TMT quantification, this came at the expense of 30%-60% fewer proteins quantified. We devised an algorithm that corrects experimental TMT ratios on the basis of determined peptide interference levels. The quantification accuracy achieved with this correction was comparable to that obtained with stringent spectrum filters but limited the loss in coverage to <10%. The generic applicability of the fold change correction algorithm was further demonstrated by spiking of chemoproteomics samples into excess amounts of E. coli tryptic digests.

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Year:  2013        PMID: 23768245     DOI: 10.1021/pr400098r

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


  89 in total

1.  Thermal proteome profiling for unbiased identification of direct and indirect drug targets using multiplexed quantitative mass spectrometry.

Authors:  Holger Franken; Toby Mathieson; Dorothee Childs; Gavain M A Sweetman; Thilo Werner; Ina Tögel; Carola Doce; Stephan Gade; Marcus Bantscheff; Gerard Drewes; Friedrich B M Reinhard; Wolfgang Huber; Mikhail M Savitski
Journal:  Nat Protoc       Date:  2015-09-17       Impact factor: 13.491

2.  Thermal proteome profiling monitors ligand interactions with cellular membrane proteins.

Authors:  Friedrich B M Reinhard; Dirk Eberhard; Thilo Werner; Holger Franken; Dorothee Childs; Carola Doce; Maria Fälth Savitski; Wolfgang Huber; Marcus Bantscheff; Mikhail M Savitski; Gerard Drewes
Journal:  Nat Methods       Date:  2015-11-02       Impact factor: 28.547

3.  Multiplexed, Quantitative Workflow for Sensitive Biomarker Discovery in Plasma Yields Novel Candidates for Early Myocardial Injury.

Authors:  Hasmik Keshishian; Michael W Burgess; Michael A Gillette; Philipp Mertins; Karl R Clauser; D R Mani; Eric W Kuhn; Laurie A Farrell; Robert E Gerszten; Steven A Carr
Journal:  Mol Cell Proteomics       Date:  2015-02-27       Impact factor: 5.911

4.  Mass Defect-Based N,N-Dimethyl Leucine Labels for Quantitative Proteomics and Amine Metabolomics of Pancreatic Cancer Cells.

Authors:  Ling Hao; Jillian Johnson; Christopher B Lietz; Amanda Buchberger; Dustin Frost; W John Kao; Lingjun Li
Journal:  Anal Chem       Date:  2017-01-04       Impact factor: 6.986

5.  Extensive Peptide Fractionation and y1 Ion-Based Interference Detection Method for Enabling Accurate Quantification by Isobaric Labeling and Mass Spectrometry.

Authors:  Mingming Niu; Ji-Hoon Cho; Kiran Kodali; Vishwajeeth Pagala; Anthony A High; Hong Wang; Zhiping Wu; Yuxin Li; Wenjian Bi; Hui Zhang; Xusheng Wang; Wei Zou; Junmin Peng
Journal:  Anal Chem       Date:  2017-02-22       Impact factor: 6.986

6.  Proteome-wide Analysis of Protein Thermal Stability in the Model Higher Plant Arabidopsis thaliana.

Authors:  Jeremy D Volkening; Kelly E Stecker; Michael R Sussman
Journal:  Mol Cell Proteomics       Date:  2018-11-06       Impact factor: 5.911

7.  Quantitative Interactome Proteomics Reveals a Molecular Basis for ATF6-Dependent Regulation of a Destabilized Amyloidogenic Protein.

Authors:  Lars Plate; Bibiana Rius; Bianca Nguyen; Joseph C Genereux; Jeffery W Kelly; R Luke Wiseman
Journal:  Cell Chem Biol       Date:  2019-05-16       Impact factor: 8.116

8.  Bayesian Confidence Intervals for Multiplexed Proteomics Integrate Ion-statistics with Peptide Quantification Concordance.

Authors:  Leonid Peshkin; Meera Gupta; Lillia Ryazanova; Martin Wühr
Journal:  Mol Cell Proteomics       Date:  2019-07-16       Impact factor: 5.911

9.  Tandem Mass Tags for Comparative and Discovery Proteomics.

Authors:  Oliver Pagel; Laxmikanth Kollipara; Albert Sickmann
Journal:  Methods Mol Biol       Date:  2021

10.  An Efficient Approach to Evaluate Reporter Ion Behavior from MALDI-MS/MS Data for Quantification Studies Using Isobaric Tags.

Authors:  Stephanie M Cologna; Christopher A Crutchfield; Brian C Searle; Paul S Blank; Cynthia L Toth; Alexa M Ely; Jaqueline A Picache; Peter S Backlund; Christopher A Wassif; Forbes D Porter; Alfred L Yergey
Journal:  J Proteome Res       Date:  2015-09-03       Impact factor: 4.466

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