A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances

被引:991
作者
Hein, Marco Y. [1 ]
Hubner, Nina C. [1 ]
Poser, Ina [2 ]
Cox, Juergen [1 ]
Nagaraj, Nagarjuna [1 ]
Toyoda, Yusuke [2 ]
Gak, Igor A. [3 ]
Weisswange, Ina [4 ,5 ]
Mansfeld, Joerg [3 ]
Buchholz, Frank [2 ,4 ]
Hyman, Anthony A. [2 ]
Mann, Matthias [1 ]
机构
[1] Max Planck Inst Biochem, D-82152 Martinsried, Germany
[2] Max Planck Inst Mol Cell Biol & Genet, D-01307 Dresden, Germany
[3] Cell Cycle, Ctr Biotechnol, D-01307 Dresden, Germany
[4] Tech Univ Dresden, Med Fac Carl Gustav Carus, UCC, Med Syst Biol, D-01307 Dresden, Germany
[5] Eupheria Biotech GmbH, D-01307 Dresden, Germany
关键词
PROTEOME-SCALE MAP; BAC TRANSGENEOMICS; COPY-NUMBER; COMPLEXES; REVEALS; ACCURATE; RESOURCE;
D O I
10.1016/j.cell.2015.09.053
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
070307 [化学生物学]; 071010 [生物化学与分子生物学];
摘要
The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries, and measure cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins and introduces a framework for quantitative network analysis.
引用
收藏
页码:712 / 723
页数:12
相关论文
共 61 条
[1]
The anaphase promoting complex/cyclosome is recruited to centromeres by the spindle assembly checkpoint [J].
Acquaviva, C ;
Herzog, F ;
Kraft, C ;
Pines, J .
NATURE CELL BIOLOGY, 2004, 6 (09) :892-U82
[2]
Error and attack tolerance of complex networks [J].
Albert, R ;
Jeong, H ;
Barabási, AL .
NATURE, 2000, 406 (6794) :378-382
[3]
Bantscheff M, 2012, ANAL BIOANAL CHEM, V404, P939, DOI 10.1007/s00216-012-6203-4
[4]
A Systematic Mammalian Genetic Interaction Map Reveals Pathways Underlying Ricin Susceptibility [J].
Bassik, Michael C. ;
Kampmann, Martin ;
Lebbink, Robert Jan ;
Wang, Shuyi ;
Hein, Marco Y. ;
Poser, Ina ;
Weibezahn, Jimena ;
Horlbeck, Max A. ;
Chen, Siyuan ;
Mann, Matthias ;
Hyman, Anthony A. ;
LeProust, Emily M. ;
McManus, Michael T. ;
Weissman, Jonathan S. .
CELL, 2013, 152 (04) :909-922
[5]
Comprehensive proteomics [J].
Beck, Martin ;
Claassen, Manfred ;
Aebersold, Ruedi .
CURRENT OPINION IN BIOTECHNOLOGY, 2011, 22 (01) :3-8
[6]
Collins BC, 2013, NAT METHODS, V10, P1246, DOI [10.1038/NMETH.2703, 10.1038/nmeth.2703]
[7]
Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae [J].
Collins, Sean R. ;
Kemmeren, Patrick ;
Zhao, Xue-Chu ;
Greenblatt, Jack F. ;
Spencer, Forrest ;
Holstege, Frank C. P. ;
Weissman, Jonathan S. ;
Krogan, Nevan J. .
MOLECULAR & CELLULAR PROTEOMICS, 2007, 6 (03) :439-450
[8]
Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ [J].
Cox, Juergen ;
Hein, Marco Y. ;
Luber, Christian A. ;
Paron, Igor ;
Nagaraj, Nagarjuna ;
Mann, Matthias .
MOLECULAR & CELLULAR PROTEOMICS, 2014, 13 (09) :2513-2526
[9]
MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification [J].
Cox, Juergen ;
Mann, Matthias .
NATURE BIOTECHNOLOGY, 2008, 26 (12) :1367-1372
[10]
Csermely P., 2006, Weak links: Stabilizers of complex systems from proteins to social networks