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This Article Full Text Full Text (PDF) Supplemental Data All Versions of this Article: M800260-MCP200v1 8/5/1130    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Glossary Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Jorge, I. Articles by Vázquez, J. Search for Related Content PubMed PubMed Citation Articles by Jorge, I. Articles by Vázquez, J. Social Bookmarking                      What's this?

Molecular & Cellular Proteomics 8:1130-1149, 2009.
© 2009 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

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^*,S

Inmaculada Jorge^,, Pedro Navarro^,, Pablo Martínez-Acedo^,,¶, Estefanía Núñez, Horacio Serrano, Arántzazu Alfranca^||, Juan Miguel Redondo^|| and Jesús Vázquez^,**

From the Centro de Biología Molecular Severo Ochoa, E-28049 Madrid, Spain and ^|| Centro Nacional de Investigaciones Cardiovasculares, E-28029 Madrid, Spain

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by ¹⁶O/¹⁸O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by ¹⁸O/¹⁶O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the ¹⁸O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins.

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