Large‐scale mapping of human protein–protein interactions by mass spectrometry

Rob M. Ewing(MaRS), Peter C. Chu(PROTO Manufacturing (Canada)), Fred Elisma(University of Ottawa), Hongyan Li, Paul Taylor, Shane Climie(Roper Technologies (United States)), Linda DB McBroom-Cerajewski(Structural Genomics Consortium), Mark D. Robinson(Walter and Eliza Hall Institute of Medical Research), Liam O’Connor(Novartis (Switzerland)), Michael Li(Integrity Testing Laboratory (Canada)), Rod S. Taylor, Moyez Dharsee(MaRS), Yuen Ho(PROTO Manufacturing (Canada)), Adrian Heilbut(Cambridge University Press), Lynda Moore(PROTO Manufacturing (Canada)), Shudong Zhang(PROTO Manufacturing (Canada)), Olga Ornatsky(University of Toronto), Yury V. Bukhman(PROTO Manufacturing (Canada)), Martin Ethier(University of Ottawa), Yinglun Sheng(University of Ottawa), Julian Vasilescu(University of Ottawa), Mohamed Abu‐Farha(University of Ottawa), Jean‐Philippe Lambert(University of Ottawa), Henry S. Duewel(PROTO Manufacturing (Canada)), Ian I. Stewart(MaRS), Bonnie Kuehl(Clinical Insights), Kelly Hogue(Hospital for Sick Children), Karen Colwill(PROTO Manufacturing (Canada)), Katharine Gladwish(PROTO Manufacturing (Canada)), Brenda Muskat(Pharma Medica Research (Canada)), Robert Kinach(University of Toronto), Sally‐Lin Adams(Hospital for Sick Children), Michael F. Moran(Hospital for Sick Children), Gregg B. Morin(PROTO Manufacturing (Canada)), Thodoros Topaloglou(University of Toronto), Daniel Figeys(University of Ottawa)
Molecular Systems Biology
March 13, 2007
Cited by 1,000Open Access
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Abstract

Mapping protein-protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein-protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24,540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein-protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.


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