Literature DB >> 22865922

Topograph, a software platform for precursor enrichment corrected global protein turnover measurements.

Edward J Hsieh1, Nicholas J Shulman, Dao-Fu Dai, Evelyn S Vincow, Pabalu P Karunadharma, Leo Pallanck, Peter S Rabinovitch, Michael J MacCoss.   

Abstract

Defects in protein turnover have been implicated in a broad range of diseases, but current proteomics methods of measuring protein turnover are limited by the software tools available. Conventional methods require indirect approaches to differentiate newly synthesized protein when synthesized from partially labeled precursor pools. To address this, we have developed Topograph, a software platform which calculates the fraction of peptides that are from newly synthesized proteins and their turnover rates. A unique feature of Topograph is the ability to calculate amino acid precursor pool enrichment levels which allows for accurate calculations when the precursor pool is not fully labeled, and the approach used by Topograph is applicable regardless of the stable isotope label used. We validate the Topograph algorithms using data acquired from a mouse labeling experiment and demonstrate the influence that precursor pool corrections can have on protein turnover measurements.

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Year:  2012        PMID: 22865922      PMCID: PMC3494182          DOI: 10.1074/mcp.O112.017699

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


  21 in total

1.  A correlation algorithm for the automated quantitative analysis of shotgun proteomics data.

Authors:  Michael J MacCoss; Christine C Wu; Hongbin Liu; Rovshan Sadygov; John R Yates
Journal:  Anal Chem       Date:  2003-12-15       Impact factor: 6.986

2.  Measurement of protein turnover in rat liver.

Authors:  R W SWICK
Journal:  J Biol Chem       Date:  1958-04       Impact factor: 5.157

3.  Proteome dynamics in complex organisms: using stable isotopes to monitor individual protein turnover rates.

Authors:  Mary K Doherty; Colin Whitehead; Heather McCormack; Simon J Gaskell; Robert J Beynon
Journal:  Proteomics       Date:  2005-02       Impact factor: 3.984

4.  Protein turnover: measurement of proteome dynamics by whole animal metabolic labelling with stable isotope labelled amino acids.

Authors:  Amy J Claydon; Michael D Thom; Jane L Hurst; Robert J Beynon
Journal:  Proteomics       Date:  2012-04       Impact factor: 3.984

5.  A data processing pipeline for mammalian proteome dynamics studies using stable isotope metabolic labeling.

Authors:  Shenheng Guan; John C Price; Stanley B Prusiner; Sina Ghaemmaghami; Alma L Burlingame
Journal:  Mol Cell Proteomics       Date:  2011-09-21       Impact factor: 5.911

6.  Rapid micromethod for determination of 15N enrichment in plasma lysine: application to measurement of whole body protein turnover.

Authors:  D M Bier; H L Christopherson
Journal:  Anal Biochem       Date:  1979-04-15       Impact factor: 3.365

Review 7.  An appraisal of techniques for the determination of protein turnover in vivo.

Authors:  P J Garlick; D J Millward
Journal:  Proc Nutr Soc       Date:  1972-12       Impact factor: 6.297

8.  Mitochondrial oxidative stress mediates angiotensin II-induced cardiac hypertrophy and Galphaq overexpression-induced heart failure.

Authors:  Dao-Fu Dai; Simon C Johnson; Jason J Villarin; Michael T Chin; Madeline Nieves-Cintrón; Tony Chen; David J Marcinek; Gerald W Dorn; Y James Kang; Tomas A Prolla; Luis F Santana; Peter S Rabinovitch
Journal:  Circ Res       Date:  2011-02-10       Impact factor: 17.367

9.  Proteome scale turnover analysis in live animals using stable isotope metabolic labeling.

Authors:  Yaoyang Zhang; Stefan Reckow; Christian Webhofer; Michael Boehme; Philipp Gormanns; Wolfgang M Egge-Jacobsen; Christoph W Turck
Journal:  Anal Chem       Date:  2011-02-11       Impact factor: 6.986

10.  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

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  31 in total

1.  Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA).

Authors:  Nicholas W Bateman; Scott P Goulding; Nicholas J Shulman; Avinash K Gadok; Karen K Szumlinski; Michael J MacCoss; Christine C Wu
Journal:  Mol Cell Proteomics       Date:  2013-07-02       Impact factor: 5.911

2.  Practical immunoaffinity-enrichment LC-MS for measuring protein kinetics of low-abundance proteins.

Authors:  Michael E Lassman; Thomas McAvoy; Anita Y H Lee; Derek Chappell; Oitak Wong; Haihong Zhou; Gissette Reyes-Soffer; Henry N Ginsberg; John S Millar; Daniel J Rader; David E Gutstein; Omar Laterza
Journal:  Clin Chem       Date:  2014-04-21       Impact factor: 8.327

3.  Respiratory chain protein turnover rates in mice are highly heterogeneous but strikingly conserved across tissues, ages, and treatments.

Authors:  Pabalu P Karunadharma; Nathan Basisty; Ying Ann Chiao; Dao-Fu Dai; Rachel Drake; Nick Levy; William J Koh; Mary J Emond; Shane Kruse; David Marcinek; Michael J Maccoss; Peter S Rabinovitch
Journal:  FASEB J       Date:  2015-05-14       Impact factor: 5.191

Review 4.  Proteome dynamics: revisiting turnover with a global perspective.

Authors:  Amy J Claydon; Robert Beynon
Journal:  Mol Cell Proteomics       Date:  2012-11-02       Impact factor: 5.911

Review 5.  What Have Mass Spectrometry-Based Proteomics and Metabolomics (Not) Taught Us about Psychiatric Disorders?

Authors:  Christoph W Turck; Michaela D Filiou
Journal:  Mol Neuropsychiatry       Date:  2015-05-12

6.  Determinants and Regulation of Protein Turnover in Yeast.

Authors:  Miguel Martin-Perez; Judit Villén
Journal:  Cell Syst       Date:  2017-09-13       Impact factor: 10.304

Review 7.  Mitochondrial protein turnover: methods to measure turnover rates on a large scale.

Authors:  X'avia C Y Chan; Caitlin M Black; Amanda J Lin; Peipei Ping; Edward Lau
Journal:  J Mol Cell Cardiol       Date:  2014-11-11       Impact factor: 5.000

8.  Proteome Dynamics from Heavy Water Metabolic Labeling and Peptide Tandem Mass Spectrometry.

Authors:  Ahmad Borzou; Vugar R Sadygov; William Zhang; Rovshan G Sadygov
Journal:  Int J Mass Spectrom       Date:  2019-07-27       Impact factor: 1.986

Review 9.  Quality control systems in cardiac aging.

Authors:  Ellen K Quarles; Dao-Fu Dai; Autumn Tocchi; Nathan Basisty; Lemuel Gitari; Peter S Rabinovitch
Journal:  Ageing Res Rev       Date:  2015-02-19       Impact factor: 10.895

10.  The PINK1-Parkin pathway promotes both mitophagy and selective respiratory chain turnover in vivo.

Authors:  Evelyn S Vincow; Gennifer Merrihew; Ruth E Thomas; Nicholas J Shulman; Richard P Beyer; Michael J MacCoss; Leo J Pallanck
Journal:  Proc Natl Acad Sci U S A       Date:  2013-03-18       Impact factor: 11.205

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