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一种以化学计量和丰度为组织特征的人类相互作用组的三个定量维度。

A human interactome in three quantitative dimensions organized by stoichiometries and abundances.

机构信息

Max Planck Institute of Biochemistry, 82152 Martinsried, Germany.

Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.

出版信息

Cell. 2015 Oct 22;163(3):712-23. doi: 10.1016/j.cell.2015.09.053.


DOI:10.1016/j.cell.2015.09.053
PMID:26496610
Abstract

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.

摘要

细胞的组织形式源于蛋白质网络的相互作用。蛋白质组网络的结构严重依赖于相互作用的强度和连接蛋白的细胞丰度,而这两者的跨度都达到了数量级。然而,这些方面尚未得到全面分析。在这里,我们构建了一个表达近内源性控制的 1125 个 GFP 标记蛋白的 HeLa 细胞系文库,作为下一代相互作用调查的输入。我们使用定量蛋白质组学来检测特定的相互作用,估计相互作用的化学计量,并测量相互作用蛋白的细胞丰度。这三个定量维度表明,蛋白质网络主要由弱的、亚化学计量的相互作用主导,这些相互作用在定义网络拓扑结构中起着关键作用。少数稳定的复合物可以通过其独特的化学计量特征来识别。本研究提供了一个丰富的相互作用数据集,连接了数千个蛋白质,并为定量网络分析引入了一个框架。

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