Literature DB >> 15359732

Global differential non-gel proteomics by quantitative and stable labeling of tryptic peptides with oxygen-18.

An Staes1, Hans Demol, Jozef Van Damme, Lennart Martens, Joël Vandekerckhove, Kris Gevaert.   

Abstract

We describe a protocol for quantitative labeling of tryptic peptides with oxygen-18. Proteins are first digested in natural water with trypsin, the pH is then lowered to 4.5 and the mixture is dried. Oxygen-18 water is added and two oxygen-18 atoms are incorporated at the peptides' carboxyl termini. Trypsin is finally inactivated by cysteine alkylation under denaturing conditions, which blocks oxygen back-exchange. The general value of this labeling strategy for differential proteomics is illustrated by the analysis and identification of several couples of differently labeled amino terminal peptides isolated from a human platelet proteome by a previously described chromatographic procedure.

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Year:  2004        PMID: 15359732     DOI: 10.1021/pr049956p

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


  19 in total

1.  A robust method for quantitative high-throughput analysis of proteomes by 18O labeling.

Authors:  Elena Bonzon-Kulichenko; Daniel Pérez-Hernández; Estefanía Núñez; Pablo Martínez-Acedo; Pedro Navarro; Marco Trevisan-Herraz; María del Carmen Ramos; Saleta Sierra; Sara Martínez-Martínez; Marisol Ruiz-Meana; Elizabeth Miró-Casas; David García-Dorado; Juan Miguel Redondo; Javier S Burgos; Jesús Vázquez
Journal:  Mol Cell Proteomics       Date:  2010-08-31       Impact factor: 5.911

2.  Minimizing back exchange in 18O/16O quantitative proteomics experiments by incorporation of immobilized trypsin into the initial digestion step.

Authors:  Joel R Sevinsky; Kristy J Brown; Benjamin J Cargile; Jonathan L Bundy; James L Stephenson
Journal:  Anal Chem       Date:  2007-01-24       Impact factor: 6.986

Review 3.  Proteomic approaches to dissect platelet function: Half the story.

Authors:  Dmitri V Gnatenko; Peter L Perrotta; Wadie F Bahou
Journal:  Blood       Date:  2006-08-22       Impact factor: 22.113

4.  CrossSearch, a user-friendly search engine for detecting chemically cross-linked peptides in conjugated proteins.

Authors:  Owen W Nadeau; Gerald J Wyckoff; Justin E Paschall; Antonio Artigues; Jessica Sage; Maria T Villar; Gerald M Carlson
Journal:  Mol Cell Proteomics       Date:  2008-02-16       Impact factor: 5.911

5.  A Bayesian Markov-chain-based heteroscedastic regression model for the analysis of 18O-labeled mass spectra.

Authors:  Qi Zhu; Tomasz Burzykowski
Journal:  J Am Soc Mass Spectrom       Date:  2011-01-15       Impact factor: 3.109

6.  Selecting protein N-terminal peptides by combined fractional diagonal chromatography.

Authors:  An Staes; Francis Impens; Petra Van Damme; Bart Ruttens; Marc Goethals; Hans Demol; Evy Timmerman; Joël Vandekerckhove; Kris Gevaert
Journal:  Nat Protoc       Date:  2011-07-14       Impact factor: 13.491

Review 7.  Proteomics dedicated to biofilmology: What have we learned from a decade of research?

Authors:  Arbia Khemiri; Thierry Jouenne; Pascal Cosette
Journal:  Med Microbiol Immunol       Date:  2015-06-12       Impact factor: 3.402

8.  Protein N-terminal acetyltransferases act as N-terminal propionyltransferases in vitro and in vivo.

Authors:  Håvard Foyn; Petra Van Damme; Svein I Støve; Nina Glomnes; Rune Evjenth; Kris Gevaert; Thomas Arnesen
Journal:  Mol Cell Proteomics       Date:  2012-10-04       Impact factor: 5.911

9.  Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach.

Authors:  Wei-Jun Qian; Matthew E Monroe; Tao Liu; Jon M Jacobs; Gordon A Anderson; Yufeng Shen; Ronald J Moore; David J Anderson; Rui Zhang; Steve E Calvano; Stephen F Lowry; Wenzhong Xiao; Lyle L Moldawer; Ronald W Davis; Ronald G Tompkins; David G Camp; Richard D Smith
Journal:  Mol Cell Proteomics       Date:  2005-03-07       Impact factor: 5.911

10.  Statistical model to analyze quantitative proteomics data obtained by 18O/16O labeling and linear ion trap mass spectrometry: application to the study of vascular endothelial growth factor-induced angiogenesis in endothelial cells.

Authors:  Inmaculada Jorge; Pedro Navarro; Pablo Martínez-Acedo; Estefanía Núñez; Horacio Serrano; Arántzazu Alfranca; Juan Miguel Redondo; Jesús Vázquez
Journal:  Mol Cell Proteomics       Date:  2009-01-29       Impact factor: 5.911

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