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酿酒酵母中蛋白质复合物的全球格局。

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae.

作者信息

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, Kanaya Shigehiko, Shilatifard Ali, O'Shea Erin, Weissman Jonathan S, Ingles C James, Hughes Timothy R, Parkinson John, Gerstein Mark, Wodak Shoshana J, Emili Andrew, Greenblatt Jack F

机构信息

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.

出版信息

Nature. 2006 Mar 30;440(7084):637-43. doi: 10.1038/nature04670. Epub 2006 Mar 22.

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.

摘要

蛋白质-蛋白质相互作用的鉴定常常能为蛋白质功能提供深入了解,并且许多细胞过程是由稳定的蛋白质复合物执行的。我们使用串联亲和纯化法处理了酿酒酵母的4562种不同的带标签蛋白质。每种制备物都通过基质辅助激光解吸/电离飞行时间质谱和液相色谱串联质谱进行分析,以提高覆盖率和准确性。利用机器学习整合质谱得分并为蛋白质-蛋白质相互作用赋予概率。在通过质谱从2357次成功纯化中高置信度鉴定出的4087种不同蛋白质中,我们的核心数据集(中位数精度为0.69)包含涉及2708种蛋白质的7123种蛋白质-蛋白质相互作用。一种马尔可夫聚类算法将这些相互作用组织成547个蛋白质复合物,每个复合物平均有4.9个亚基,其中约一半在MIPS数据库中不存在,还有429种复合物对之间的额外相互作用。这些数据(所有数据均可在线获取)将有助于未来对单个蛋白质以及功能基因组学和系统生物学的研究。

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