Global landscape of protein complexes in the yeast Saccharomyces cerevisiae |
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Authors: | Krogan Nevan J Cagney Gerard Yu Haiyuan Zhong Gouqing Guo Xinghua Ignatchenko Alexandr Li Joyce Pu Shuye Datta Nira Tikuisis Aaron P Punna Thanuja Peregrín-Alvarez José M Shales Michael Zhang Xin Davey Michael Robinson Mark D Paccanaro Alberto Bray James E Sheung Anthony Beattie Bryan Richards Dawn P Canadien Veronica Lalev Atanas Mena Frank Wong Peter Starostine Andrei Canete Myra M Vlasblom James Wu Samuel Orsi Chris Collins Sean R Chandran Shamanta Haw Robin Rilstone Jennifer J Gandi Kiran Thompson Natalie J Musso Gabe St Onge Peter Ghanny Shaun Lam Mandy H Y Butland Gareth Altaf-Ul Amin M |
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Affiliation: | Banting and Best Department of Medical Research, Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College St, Toronto, Ontario M5S 3E1, Canada. |
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Abstract: | Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology. |
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