Literature DB >> 22457332

Hyperplexing: a method for higher-order multiplexed quantitative proteomics provides a map of the dynamic response to rapamycin in yeast.

Noah Dephoure1, Steven P Gygi.   

Abstract

Large-scale quantitative proteomics can provide a near-global view of cellular protein abundance. Yet, the time, effort, and expertise required to achieve reasonable protein coverage and reliable quantification have limited the broad application of this technology. To fully leverage mass spectrometry for the elucidation of biological systems requires sufficient throughput to monitor dynamic changes across conditions and to enable replicate analysis to provide statistical power. We report a straightforward approach to increase the multiplexing capacity of quantitative mass spectrometry, which provides a platform for the analysis of cellular signaling pathways. Using triplex metabolic labeling and six-plex isobaric tags, we monitored changes in protein abundance from 18 samples simultaneously, performing biological triplicates of a six-point time course of rapamycin-stimulated yeast. The data set provides temporal abundance profiles for thousands of yeast proteins, highlighting the complex cellular roles of the TOR (target of rapamycin) pathway.

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Year:  2012        PMID: 22457332      PMCID: PMC5292868          DOI: 10.1126/scisignal.2002548

Source DB:  PubMed          Journal:  Sci Signal        ISSN: 1945-0877            Impact factor:   8.192


  24 in total

1.  Clustering gene expression patterns.

Authors:  A Ben-Dor; R Shamir; Z Yakhini
Journal:  J Comput Biol       Date:  1999 Fall-Winter       Impact factor: 1.479

2.  Identification of direct and indirect targets of the Gln3 and Gat1 activators by transcriptional profiling in response to nitrogen availability in the short and long term.

Authors:  Bart Scherens; André Feller; Fabienne Vierendeels; Francine Messenguy; Evelyne Dubois
Journal:  FEMS Yeast Res       Date:  2006-08       Impact factor: 2.796

3.  Delayed correlation of mRNA and protein expression in rapamycin-treated cells and a role for Ggc1 in cellular sensitivity to rapamycin.

Authors:  Marjorie L Fournier; Ariel Paulson; Norman Pavelka; Amber L Mosley; Karin Gaudenz; William D Bradford; Earl Glynn; Hua Li; Mihaela E Sardiu; Brian Fleharty; Christopher Seidel; Laurence Florens; Michael P Washburn
Journal:  Mol Cell Proteomics       Date:  2009-11-10       Impact factor: 5.911

4.  Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics.

Authors:  Blagoy Blagoev; Shao-En Ong; Irina Kratchmarova; Matthias Mann
Journal:  Nat Biotechnol       Date:  2004-08-15       Impact factor: 54.908

5.  Global analysis of protein expression in yeast.

Authors:  Sina Ghaemmaghami; Won-Ki Huh; Kiowa Bower; Russell W Howson; Archana Belle; Noah Dephoure; Erin K O'Shea; Jonathan S Weissman
Journal:  Nature       Date:  2003-10-16       Impact factor: 49.962

6.  The SCX/IMAC enrichment approach for global phosphorylation analysis by mass spectrometry.

Authors:  Judit Villén; Steven P Gygi
Journal:  Nat Protoc       Date:  2008       Impact factor: 13.491

7.  Identification of aneuploidy-tolerating mutations.

Authors:  Eduardo M Torres; Noah Dephoure; Amudha Panneerselvam; Cheryl M Tucker; Charles A Whittaker; Steven P Gygi; Maitreya J Dunham; Angelika Amon
Journal:  Cell       Date:  2010-09-16       Impact factor: 41.582

8.  MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics.

Authors:  Lily Ting; Ramin Rad; Steven P Gygi; Wilhelm Haas
Journal:  Nat Methods       Date:  2011-10-02       Impact factor: 28.547

9.  High-Throughput GoMiner, an 'industrial-strength' integrative gene ontology tool for interpretation of multiple-microarray experiments, with application to studies of Common Variable Immune Deficiency (CVID).

Authors:  Barry R Zeeberg; Haiying Qin; Sudarshan Narasimhan; Margot Sunshine; Hong Cao; David W Kane; Mark Reimers; Robert M Stephens; David Bryant; Stanley K Burt; Eldad Elnekave; Danielle M Hari; Thomas A Wynn; Charlotte Cunningham-Rundles; Donn M Stewart; David Nelson; John N Weinstein
Journal:  BMC Bioinformatics       Date:  2005-07-05       Impact factor: 3.169

10.  Optimized protein extraction for quantitative proteomics of yeasts.

Authors:  Tobias von der Haar
Journal:  PLoS One       Date:  2007-10-24       Impact factor: 3.240

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  62 in total

Review 1.  A Biologist's Field Guide to Multiplexed Quantitative Proteomics.

Authors:  Corey E Bakalarski; Donald S Kirkpatrick
Journal:  Mol Cell Proteomics       Date:  2016-02-12       Impact factor: 5.911

2.  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

Review 3.  Quantifying proteomes and their post-translational modifications by stable isotope label-based mass spectrometry.

Authors:  Anna E Merrill; Joshua J Coon
Journal:  Curr Opin Chem Biol       Date:  2013-07-05       Impact factor: 8.822

4.  Multiscale analysis of the murine intestine for modeling human diseases.

Authors:  Jesse Lyons; Charles A Herring; Amrita Banerjee; Alan J Simmons; Ken S Lau
Journal:  Integr Biol (Camb)       Date:  2015-07       Impact factor: 2.192

Review 5.  Quantifying ubiquitin signaling.

Authors:  Alban Ordureau; Christian Münch; J Wade Harper
Journal:  Mol Cell       Date:  2015-05-21       Impact factor: 17.970

Review 6.  Quantitative proteomic analysis of histone modifications.

Authors:  He Huang; Shu Lin; Benjamin A Garcia; Yingming Zhao
Journal:  Chem Rev       Date:  2015-02-17       Impact factor: 60.622

7.  Time-resolved Analysis of Proteome Dynamics by Tandem Mass Tags and Stable Isotope Labeling in Cell Culture (TMT-SILAC) Hyperplexing.

Authors:  Kevin A Welle; Tian Zhang; Jennifer R Hryhorenko; Shichen Shen; Jun Qu; Sina Ghaemmaghami
Journal:  Mol Cell Proteomics       Date:  2016-10-20       Impact factor: 5.911

Review 8.  Next-generation proteomics: towards an integrative view of proteome dynamics.

Authors:  A F Maarten Altelaar; Javier Munoz; Albert J R Heck
Journal:  Nat Rev Genet       Date:  2012-12-04       Impact factor: 53.242

9.  Enhanced Sample Multiplexing of Tissues Using Combined Precursor Isotopic Labeling and Isobaric Tagging (cPILOT).

Authors:  Christina D King; Joseph D Dudenhoeffer; Liqing Gu; Adam R Evans; Renã A S Robinson
Journal:  J Vis Exp       Date:  2017-05-01       Impact factor: 1.355

10.  Accurate multiplexed proteomics at the MS2 level using the complement reporter ion cluster.

Authors:  Martin Wühr; Wilhelm Haas; Graeme C McAlister; Leonid Peshkin; Ramin Rad; Marc W Kirschner; Steven P Gygi
Journal:  Anal Chem       Date:  2012-10-25       Impact factor: 6.986

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