Architecture of the human interactome defines protein communities and disease networks.
Architecture of the human interactome defines protein communities and disease networks.
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DOI：
10.1038/nature22366
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发表时间：
2017-05-25
期刊：
影响因子：
64.8
通讯作者：
Harper JW
中科院分区：
文献类型：
--
作者：
Huttlin EL;Bruckner RJ;Paulo JA;Cannon JR;Ting L;Baltier K;Colby G;Gebreab F;Gygi MP;Parzen H;Szpyt J;Tam S;Zarraga G;Pontano-Vaites L;Swarup S;White AE;Schweppe DK;Rad R;Erickson BK;Obar RA;Guruharsha KG;Li K;Artavanis-Tsakonas S;Gygi SP;Harper JW
细胞的生理学可以被视为数千种蛋白质共同作用的产物，以塑造细胞的反应。协调部分是通过蛋白质-蛋白质相互作用网络实现的，这些网络将功能相关的蛋白质组装成复合体、细胞器和信号转导通路。了解人类蛋白质组的结构有可能为细胞、结构和进化机制提供信息，并对阐明基因组变异如何导致疾病至关重要。在这里，我们介绍了BioPlex 2.0(ORFEOME衍生复合体的生物物理相互作用)，它使用强大的亲和纯化-质谱学(AP-MS)方法来阐明由超过25%的人类基因组编码基因组成的蛋白质相互作用网络和共复合体，构成了迄今为止最大的此类网络。通过56,000个候选相互作用，BioPlex 2.0包含29,000个以前未知的共关联，并提供对数百种特性不佳的蛋白质的功能洞察，同时增强对结构域关联、亚细胞定位和共复合体形成的基于网络的分析。相互作用蛋白质的无监督马尔可夫聚类(MCL)确定了1300多个代表不同细胞活动的蛋白质群落。细胞健康所必需的基因在代表中央细胞功能的53个社区中得到丰富。此外，我们确定了与2000多个疾病注释相关的442个社区，将许多候选疾病基因放入一个细胞框架中。BioPlex 2.0在深度和广度上超过了以前实验得出的相互作用网络，将是探索未完全表征的蛋白质的生物学和阐明蛋白质组组织的更大规模模式的宝贵资源。
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 elucidation of how genome variation contributes to disease. Here, we present BioPlex 2.0 (Biophysical Interactions of ORFEOME-derived complexes), which employs robust affinity purification-mass spectrometry (AP-MS) methodology to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein coding genes from the human genome, and constitutes the largest such network to date. With >56,000 candidate interactions, BioPlex 2.0 contains >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 (MCL) of interacting proteins identified more than 1300 protein communities representing diverse cellular activities. Genes essential for cell fitness are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2000 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.
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影响因子：
10.5
作者：
Meng Z;Moroishi T;Guan KL
通讯作者：
Guan KL
影响因子：
64.5
作者：
Huttlin EL;Jedrychowski MP;Elias JE;Goswami T;Rad R;Beausoleil SA;Villén J;Haas W;Sowa ME;Gygi SP
通讯作者：
Gygi SP
影响因子：
14.9
作者：
Chatr-Aryamontri A;Breitkreutz BJ;Heinicke S;Boucher L;Winter A;Stark C;Nixon J;Ramage L;Kolas N;O'Donnell L;Reguly T;Breitkreutz A;Sellam A;Chen D;Chang C;Rust J;Livstone M;Oughtred R;Dolinski K;Tyers M
通讯作者：
Tyers M
影响因子：
56.9
作者：
Blomen, Vincent A.;Majek, Peter;Brummelkamp, Thijn R.
通讯作者：
Brummelkamp, Thijn R.
影响因子：
4.6
作者：
Gallegos LL;Ng MR;Sowa ME;Selfors LM;White A;Zervantonakis IK;Singh P;Dhakal S;Harper JW;Brugge JS
通讯作者：
Brugge JS