Architecture of the human interactome defines protein communities and disease networks

被引:1003
作者
Huttlin, Edward L. [1 ]
Bruckner, Raphael J. [1 ]
Paulo, Joao A. . [1 ]
Cannon, Joe R. [1 ]
Ting, Lily [1 ]
Baltier, Kurt [1 ]
Colby, Greg [1 ]
Gebreab, Fana [1 ]
Gygi, Melanie P. [1 ]
Parzen, Hannah [1 ]
Szpyt, John [1 ]
Tam, Stanley [1 ]
Zarraga, Gabriela [1 ]
Pontano-Vaites, Laura [1 ]
Swarup, Sharan [1 ]
White, Anne E. [1 ]
Schweppe, Devin K. [1 ]
Rad, Ramin [1 ]
Erickson, Brian K. [1 ]
Obar, Robert A. . [2 ]
Guruharsha, K. G. [2 ]
Li, Kejie [2 ]
Rtavanis-Tsakonas, Spyros A. [1 ,2 ]
Gygi, Steven P. [1 ]
Harper, J. Wade [1 ]
机构
[1] Harvard Med Sch, Dept Cell Biol, Boston, MA 02115 USA
[2] Biogen Inc, 250 Binney St, Cambridge, MA 02142 USA
基金
美国国家卫生研究院;
关键词
SCALE MAP; REGULATORS; LANDSCAPE; COMPLEXES; PEPTIDES;
D O I
10.1038/nature22366
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease(1-3). Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification-mass spectrometry methodology(4) to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering(5) of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness(6,7) are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.
引用
收藏
页码:505 / +
页数:21
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