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大量的辅助蛋白互作网络在不同环境中被重新布线。

A large accessory protein interactome is rewired across environments.

机构信息

Department of Biochemistry, Stony Brook University, Stony Brook, United States.

Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, United States.

出版信息

Elife. 2020 Sep 14;9:e62365. doi: 10.7554/eLife.62365.

DOI:10.7554/eLife.62365
PMID:32924934
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7577743/
Abstract

To characterize how protein-protein interaction (PPI) networks change, we quantified the relative PPI abundance of 1.6 million protein pairs in the yeast across nine growth conditions, with replication, for a total of 44 million measurements. Our multi-condition screen identified 13,764 pairwise PPIs, a threefold increase over PPIs identified in one condition. A few 'immutable' PPIs are present across all conditions, while most 'mutable' PPIs are rarely observed. Immutable PPIs aggregate into highly connected 'core' network modules, with most network remodeling occurring within a loosely connected 'accessory' module. Mutable PPIs are less likely to co-express, co-localize, and be explained by simple mass action kinetics, and more likely to contain proteins with intrinsically disordered regions, implying that environment-dependent association and binding is critical to cellular adaptation. Our results show that protein interactomes are larger than previously thought and contain highly dynamic regions that reorganize to drive or respond to cellular changes.

摘要

为了描述蛋白质-蛋白质相互作用(PPI)网络的变化,我们在 9 种生长条件下对酵母中的 160 万个蛋白质对进行了相对 PPI 丰度的定量分析,共进行了 4400 万次测量。我们的多条件筛选鉴定了 13764 对 PPI,比在一种条件下鉴定的 PPI 增加了三倍。一些“不变”的 PPI 存在于所有条件下,而大多数“可变”的 PPI 很少被观察到。不变的 PPI 聚集到高度连接的“核心”网络模块中,大多数网络重塑发生在松散连接的“附属”模块内。可变的 PPI 不太可能共同表达、共定位,也不太可能被简单的质量作用动力学解释,而且更有可能包含具有内在无序区域的蛋白质,这意味着环境依赖的关联和结合对细胞适应至关重要。我们的结果表明,蛋白质相互作用组比以前想象的要大,并且包含高度动态的区域,这些区域会重新组织以驱动或响应细胞变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/1f7ed70c8562/elife-62365-fig3-figsupp3.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/1f7ed70c8562/elife-62365-fig3-figsupp3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/587ce12e6402/elife-62365-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/2c5275329ec5/elife-62365-fig1-figsupp1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/8cea2707f6d1/elife-62365-fig1-figsupp2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/2388655b79a0/elife-62365-fig1-figsupp3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/588551dae1f1/elife-62365-fig1-figsupp4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/6e273b948cbf/elife-62365-fig1-figsupp5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/d6b80f5be326/elife-62365-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/e7700b2a9722/elife-62365-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1e6/7577743/1742e9d17d0a/elife-62365-fig3-figsupp2.jpg
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3
iSeq 2.0: A Modular and Interchangeable Toolkit for Interaction Screening in Yeast.iSeq 2.0:酵母相互作用筛选的模块化可互换工具包。
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