Literature DB >> 23334424

A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis.

Paola Picotti1, Mathieu Clément-Ziza, Henry Lam, David S Campbell, Alexander Schmidt, Eric W Deutsch, Hannes Röst, Zhi Sun, Oliver Rinner, Lukas Reiter, Qin Shen, Jacob J Michaelson, Andreas Frei, Simon Alberti, Ulrike Kusebauch, Bernd Wollscheid, Robert L Moritz, Andreas Beyer, Ruedi Aebersold.   

Abstract

Experience from different fields of life sciences suggests that accessible, complete reference maps of the components of the system under study are highly beneficial research tools. Examples of such maps include libraries of the spectroscopic properties of molecules, or databases of drug structures in analytical or forensic chemistry. Such maps, and methods to navigate them, constitute reliable assays to probe any sample for the presence and amount of molecules contained in the map. So far, attempts to generate such maps for any proteome have failed to reach complete proteome coverage. Here we use a strategy based on high-throughput peptide synthesis and mass spectrometry to generate an almost complete reference map (97% of the genome-predicted proteins) of the Saccharomyces cerevisiae proteome. We generated two versions of this mass-spectrometric map, one supporting discovery-driven (shotgun) and the other supporting hypothesis-driven (targeted) proteomic measurements. Together, the two versions of the map constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. To show the utility of the maps, we applied them to a protein quantitative trait locus (QTL) analysis, which requires precise measurement of the same set of peptides over a large number of samples. Protein measurements over 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, influencing the levels of related proteins. Our results suggest that selective pressure favours the acquisition of sets of polymorphisms that adapt protein levels but also maintain the stoichiometry of functionally related pathway members.

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Year:  2013        PMID: 23334424      PMCID: PMC3951219          DOI: 10.1038/nature11835

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  70 in total

1.  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

2.  Using annotated peptide mass spectrum libraries for protein identification.

Authors:  R Craig; J C Cortens; D Fenyo; R C Beavis
Journal:  J Proteome Res       Date:  2006-08       Impact factor: 4.466

3.  Development and validation of a spectral library searching method for peptide identification from MS/MS.

Authors:  Henry Lam; Eric W Deutsch; James S Eddes; Jimmy K Eng; Nichole King; Stephen E Stein; Ruedi Aebersold
Journal:  Proteomics       Date:  2007-03       Impact factor: 3.984

4.  Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

Authors:  Vinzenz Lange; Johan A Malmström; John Didion; Nichole L King; Björn P Johansson; Juliane Schäfer; Jonathan Rameseder; Chee-Hong Wong; Eric W Deutsch; Mi-Youn Brusniak; Peter Bühlmann; Lars Björck; Bruno Domon; Ruedi Aebersold
Journal:  Mol Cell Proteomics       Date:  2008-04-13       Impact factor: 5.911

5.  An integrated, directed mass spectrometric approach for in-depth characterization of complex peptide mixtures.

Authors:  Alexander Schmidt; Nils Gehlenborg; Bernd Bodenmiller; Lukas N Mueller; Dave Campbell; Markus Mueller; Ruedi Aebersold; Bruno Domon
Journal:  Mol Cell Proteomics       Date:  2008-05-29       Impact factor: 5.911

6.  High-throughput generation of selected reaction-monitoring assays for proteins and proteomes.

Authors:  Paola Picotti; Oliver Rinner; Robert Stallmach; Franziska Dautel; Terry Farrah; Bruno Domon; Holger Wenschuh; Ruedi Aebersold
Journal:  Nat Methods       Date:  2009-12-06       Impact factor: 28.547

7.  The focusing positions of polypeptides in immobilized pH gradients can be predicted from their amino acid sequences.

Authors:  B Bjellqvist; G J Hughes; C Pasquali; N Paquet; F Ravier; J C Sanchez; S Frutiger; D Hochstrasser
Journal:  Electrophoresis       Date:  1993-10       Impact factor: 3.535

8.  Comparative analysis of proteome and transcriptome variation in mouse.

Authors:  Anatole Ghazalpour; Brian Bennett; Vladislav A Petyuk; Luz Orozco; Raffi Hagopian; Imran N Mungrue; Charles R Farber; Janet Sinsheimer; Hyun M Kang; Nicholas Furlotte; Christopher C Park; Ping-Zi Wen; Heather Brewer; Karl Weitz; David G Camp; Calvin Pan; Roumyana Yordanova; Isaac Neuhaus; Charles Tilford; Nathan Siemers; Peter Gargalovic; Eleazar Eskin; Todd Kirchgessner; Desmond J Smith; Richard D Smith; Aldons J Lusis
Journal:  PLoS Genet       Date:  2011-06-09       Impact factor: 5.917

9.  The PeptideAtlas project.

Authors:  Frank Desiere; Eric W Deutsch; Nichole L King; Alexey I Nesvizhskii; Parag Mallick; Jimmy Eng; Sharon Chen; James Eddes; Sandra N Loevenich; Ruedi Aebersold
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

10.  Absolute quantification of microbial proteomes at different states by directed mass spectrometry.

Authors:  Alexander Schmidt; Martin Beck; Johan Malmström; Henry Lam; Manfred Claassen; David Campbell; Ruedi Aebersold
Journal:  Mol Syst Biol       Date:  2011-07-19       Impact factor: 11.429

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  125 in total

1.  Quantitative mass spectrometry-based multiplexing compares the abundance of 5000 S. cerevisiae proteins across 10 carbon sources.

Authors:  Joao A Paulo; Jeremy D O'Connell; Robert A Everley; Jonathon O'Brien; Micah A Gygi; Steven P Gygi
Journal:  J Proteomics       Date:  2016-07-16       Impact factor: 4.044

2.  Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system.

Authors:  Ben C Collins; Ludovic C Gillet; George Rosenberger; Hannes L Röst; Anton Vichalkovski; Matthias Gstaiger; Ruedi Aebersold
Journal:  Nat Methods       Date:  2013-10-27       Impact factor: 28.547

Review 3.  Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases.

Authors:  Yan V Sun; Yi-Juan Hu
Journal:  Adv Genet       Date:  2016-01-25       Impact factor: 1.944

4.  Emerging mass spectrometry techniques for the direct analysis of microbial colonies.

Authors:  Jinshu Fang; Pieter C Dorrestein
Journal:  Curr Opin Microbiol       Date:  2014-07-26       Impact factor: 7.934

5.  Genome-Wide Association Mapping Reveals That Specific and Pleiotropic Regulatory Mechanisms Fine-Tune Central Metabolism and Growth in Arabidopsis.

Authors:  Corina M Fusari; Rik Kooke; Martin A Lauxmann; Maria Grazia Annunziata; Beatrice Enke; Melanie Hoehne; Nicole Krohn; Frank F M Becker; Armin Schlereth; Ronan Sulpice; Mark Stitt; Joost J B Keurentjes
Journal:  Plant Cell       Date:  2017-09-27       Impact factor: 11.277

6.  Antibody-independent targeted quantification of TMPRSS2-ERG fusion protein products in prostate cancer.

Authors:  Jintang He; Xuefei Sun; Tujin Shi; Athena A Schepmoes; Thomas L Fillmore; Vladislav A Petyuk; Fang Xie; Rui Zhao; Marina A Gritsenko; Feng Yang; Naoki Kitabayashi; Sung-Suk Chae; Mark A Rubin; Javed Siddiqui; John T Wei; Arul M Chinnaiyan; Wei-Jun Qian; Richard D Smith; Jacob Kagan; Sudhir Srivastava; Karin D Rodland; Tao Liu; David G Camp
Journal:  Mol Oncol       Date:  2014-02-21       Impact factor: 6.603

7.  A random forest approach to capture genetic effects in the presence of population structure.

Authors:  Johannes Stephan; Oliver Stegle; Andreas Beyer
Journal:  Nat Commun       Date:  2015-06-25       Impact factor: 14.919

8.  A robust and efficient method for estimating enzyme complex abundance and metabolic flux from expression data.

Authors:  Narayanan Sadagopan; Yiping Wang; Brandon E Barker; Kieran Smallbone; Christopher R Myers; Hongwei Xi; Jason W Locasale; Zhenglong Gu
Journal:  Comput Biol Chem       Date:  2015-09-01       Impact factor: 2.877

Review 9.  The future of whole-cell modeling.

Authors:  Derek N Macklin; Nicholas A Ruggero; Markus W Covert
Journal:  Curr Opin Biotechnol       Date:  2014-02-17       Impact factor: 9.740

10.  Using PeptideAtlas, SRMAtlas, and PASSEL: Comprehensive Resources for Discovery and Targeted Proteomics.

Authors:  Ulrike Kusebauch; Eric W Deutsch; David S Campbell; Zhi Sun; Terry Farrah; Robert L Moritz
Journal:  Curr Protoc Bioinformatics       Date:  2014-06-17
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