Literature DB >> 17322307

Improved method for differential expression proteomics using trypsin-catalyzed 18O labeling with a correction for labeling efficiency.

Antonio Ramos-Fernández1, Daniel López-Ferrer, Jesús Vázquez.   

Abstract

Quantitative strategies relying on stable isotope labeling and isotope dilution mass spectrometry have proven to be a very robust alternative to the well established gel-based techniques for the study of the dynamic proteome. Postdigestion 18O labeling is becoming very popular mainly due to the simplicity of the enzyme-catalyzed exchange reaction, the peptide handling and storage procedures, and the flexibility and versatility introduced by decoupling protein digestion from peptide labeling. Despite recent progresses, peptide quantification by postdigestion 18O labeling still involves several computational problems. In this work we analyzed the behavior of large collections of peptides when they were subjected to postdigestion labeling and concluded that this process can be explained by a universal kinetic model. On the basis of this observation, we developed an advanced quantification algorithm for this kind of labeling. Our method fits the entire isotopic envelope to parameters related with the kinetic exchange model, allowing at the same time an accurate calculation of the relative proportion of peptides in the original samples and of the specific labeling efficiency of each one of the peptides. We demonstrated that the new method eliminates artifacts produced by incomplete oxygen exchange in subsets of peptides that have a relatively low labeling efficiency and that may be considered indicative of false protein ratio deviations. Finally using a rigorous statistical analysis based on the calculation of error rates associated with false expression changes, we showed the validity of the method in the practice by detecting significant expression changes, produced by the activation of a model preparation of T cells, with only 5 microg of protein in three proteins among a pool of more than 100. By allowing a full control over potential artifacts, our method may improve automation of the procedures for relative protein quantification using this labeling strategy.

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Year:  2007        PMID: 17322307     DOI: 10.1074/mcp.T600029-MCP200

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


  28 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.  A novel strategy for global analysis of the dynamic thiol redox proteome.

Authors:  Pablo Martínez-Acedo; Estefanía Núñez; Francisco J Sánchez Gómez; Margoth Moreno; Elena Ramos; Alicia Izquierdo-Álvarez; Elisabet Miró-Casas; Raquel Mesa; Patricia Rodriguez; Antonio Martínez-Ruiz; David Garcia Dorado; Santiago Lamas; Jesús Vázquez
Journal:  Mol Cell Proteomics       Date:  2012-05-30       Impact factor: 5.911

Review 3.  18O stable isotope labeling in MS-based proteomics.

Authors:  Xiaoying Ye; Brian Luke; Thorkell Andresson; Josip Blonder
Journal:  Brief Funct Genomic Proteomic       Date:  2009-01-16

Review 4.  Liquid chromatography-mass spectrometry-based quantitative proteomics.

Authors:  Fang Xie; Tao Liu; Wei-Jun Qian; Vladislav A Petyuk; Richard D Smith
Journal:  J Biol Chem       Date:  2011-06-01       Impact factor: 5.157

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.  Quantification of isotopically overlapping deamidated and 18o-labeled peptides using isotopic envelope mixture modeling.

Authors:  Surendra Dasari; Phillip A Wilmarth; Ashok P Reddy; Lucinda J G Robertson; Srinivasa R Nagalla; Larry L David
Journal:  J Proteome Res       Date:  2009-03       Impact factor: 4.466

7.  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

8.  18O proteomics reveal increased human apolipoprotein CIII in Hispanic HIV-1+ women with HAART that use cocaine.

Authors:  Frances Zenón; Inmaculada Jorge; Ailed Cruz; Erick Suárez; Annabell C Segarra; Jesús Vázquez; Loyda M Meléndez; Horacio Serrano
Journal:  Proteomics Clin Appl       Date:  2015-11-19       Impact factor: 3.494

9.  Decon2LS: An open-source software package for automated processing and visualization of high resolution mass spectrometry data.

Authors:  Navdeep Jaitly; Anoop Mayampurath; Kyle Littlefield; Joshua N Adkins; Gordon A Anderson; Richard D Smith
Journal:  BMC Bioinformatics       Date:  2009-03-17       Impact factor: 3.169

10.  Robust MS quantification method for phospho-peptides using 18O/16O labeling.

Authors:  Claus A Andersen; Stefano Gotta; Letizia Magnoni; Roberto Raggiaschi; Andreas Kremer; Georg C Terstappen
Journal:  BMC Bioinformatics       Date:  2009-05-11       Impact factor: 3.169

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