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人类相互作用组的架构定义了蛋白质群落和疾病网络。

Architecture of the human interactome defines protein communities and disease networks.

作者信息

Huttlin Edward L, Bruckner Raphael J, Paulo Joao A, Cannon Joe R, Ting Lily, Baltier Kurt, Colby Greg, Gebreab Fana, Gygi Melanie P, Parzen Hannah, Szpyt John, Tam Stanley, Zarraga Gabriela, Pontano-Vaites Laura, Swarup Sharan, White Anne E, Schweppe Devin K, Rad Ramin, Erickson Brian K, Obar Robert A, Guruharsha K G, Li Kejie, Artavanis-Tsakonas Spyros, Gygi Steven P, Harper J Wade

机构信息

Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, USA.

Biogen Inc., 250 Binney Street, Cambridge, Massachusetts 02142, USA.

出版信息

Nature. 2017 May 25;545(7655):505-509. doi: 10.1038/nature22366. Epub 2017 May 17.


DOI:10.1038/nature22366
PMID:28514442
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5531611/
Abstract

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. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification-mass spectrometry methodology 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 of interacting proteins identified more than 1,300 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 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.

摘要

细胞的生理学可被视为数千种蛋白质协同作用以塑造细胞反应的产物。部分协调是通过蛋白质 - 蛋白质相互作用网络实现的,该网络将功能相关的蛋白质组装成复合物、细胞器和信号转导途径。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,对于阐明基因组变异如何导致疾病至关重要。在此,我们展示BioPlex 2.0(开放阅读框来源复合物的生物物理相互作用),它使用强大的亲和纯化 - 质谱方法来阐明蛋白质相互作用网络以及由人类基因组中超过25%的蛋白质编码基因形成的共复合物,据我们所知,这是迄今为止最大的此类网络。BioPlex 2.0有超过56,000个候选相互作用,包含超过29,000个先前未知的共关联,并为数百种特征不明确的蛋白质提供功能见解,同时增强基于网络的结构域关联、亚细胞定位和共复合物形成分析。对相互作用蛋白质进行无监督马尔可夫聚类识别出1300多个代表不同细胞活动的蛋白质群落。对细胞适应性至关重要的基因在代表核心细胞功能的53个群落中富集。此外,我们鉴定出与2000多个疾病注释相关的442个群落,将众多候选疾病基因置于细胞框架中。BioPlex 2.0在深度和广度上超过了以前通过实验得出的相互作用网络,将成为探索特征不完全明确的蛋白质生物学以及阐明蛋白质组组织更大规模模式的宝贵资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/2459d2dda2e7/nihms867766f14.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/2459d2dda2e7/nihms867766f14.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/1cdef5eec6bc/nihms867766f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/f2037e1d6095/nihms867766f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/c347eb51bfb6/nihms867766f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/5137e8d31e50/nihms867766f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/b52233f08134/nihms867766f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/f526b0ee193d/nihms867766f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/bb751be54ea0/nihms867766f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/4caa9843c75c/nihms867766f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/5c3a89cd4f5b/nihms867766f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/d393bf051a11/nihms867766f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42fa/5531611/2459d2dda2e7/nihms867766f14.jpg

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