Novel biochemical, structural, and systems insights into inflammatory signaling revealed by contextual interaction proteomics.
Novel biochemical, structural, and systems insights into inflammatory signaling revealed by contextual interaction proteomics.
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DOI：
10.1073/pnas.2117175119
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发表时间：
2022-10-04
影响因子：
11.1
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中科院分区：
文献类型：
--
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在这项工作中，我们提出了一个转变，我们分析和概念化蛋白质-蛋白质相互作用（PPI）网络的方式。我们提出了一个实验和计算的框架来模拟它们在细胞的上下文中。我们将这一框架应用于信号体肿瘤坏死因子受体信号复合物（TNF-RSC），并生成了一个其形成和结构的综合模型，该模型提供了有关其组织和调控的见解并解决了争议。为了实现这一目标，我们首先开发和优化的方法来映射目标复合物的组成，其绝对化学计量，其组装动力学，其对信号的时间依赖性，以及其对表达的蛋白质组的依赖性。蛋白质-蛋白质相互作用（PPI）代表了细胞中蛋白质组组织的主要模式。在过去的十年中，PPI网络的几种大规模表示已经捕获了网络组件功能组织的一般方面，但大多缺乏蜂窝状态的背景。然而，生成上下文相关的PPI网络是必不可少的结构和系统级建模的生物过程的目标，仍然是一个未解决的挑战。在这里，我们描述了一个实验/计算策略，以实现PPI的建模，考虑上下文信息。该策略定义了目标组件形成的组成、化学计量、时间组织和细胞要求。我们使用这种方法来生成一个大的信号体，TNF受体信号复合物（TNF-RSC）的形成原理和架构的集成模型。总体而言，我们表明，系统和结构水平的信息的整合提供了一个通用的，在很大程度上未开发的模块化蛋白质组和细胞功能之间的联系。
In this work, we propose a shift in the way we analyze and conceptualize protein–protein interaction (PPI) networks. We present an experimental and computational framework to model them in the cellular context. We applied this framework to the signalosome tumor necrosis factor–receptor signaling complex (TNF-RSC) and generated an integrated model of its formation and architecture that provides insights and resolved controversies regarding its organization and regulation. To achieve this, we first developed and optimized approaches to map the composition of a target complex, its absolute stoichiometry, its assembly dynamics, its temporal dependence on signaling, and its reliance on the expressed proteome. Protein–protein interactions (PPIs) represent the main mode of the proteome organization in the cell. In the last decade, several large-scale representations of PPI networks have captured generic aspects of the functional organization of network components but mostly lack the context of cellular states. However, the generation of context-dependent PPI networks is essential for structural and systems-level modeling of biological processes—a goal that remains an unsolved challenge. Here we describe an experimental/computational strategy to achieve a modeling of PPIs that considers contextual information. This strategy defines the composition, stoichiometry, temporal organization, and cellular requirements for the formation of target assemblies. We used this approach to generate an integrated model of the formation principles and architecture of a large signalosome, the TNF–receptor signaling complex (TNF-RSC). Overall, we show that the integration of systems- and structure-level information provides a generic, largely unexplored link between the modular proteome and cellular function.
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影响因子：
64.8
作者：
Kim SJ;Fernandez-Martinez J;Nudelman I;Shi Y;Zhang W;Raveh B;Herricks T;Slaughter BD;Hogan JA;Upla P;Chemmama IE;Pellarin R;Echeverria I;Shivaraju M;Chaudhury AS;Wang J;Williams R;Unruh JR;Greenberg CH;Jacobs EY;Yu Z;de la Cruz MJ;Mironska R;Stokes DL;Aitchison JD;Jarrold MF;Gerton JL;Ludtke SJ;Akey CW;Chait BT;Sali A;Rout MP
通讯作者：
Rout MP
影响因子：
8.8
作者：
Fujita H;Tokunaga A;Shimizu S;Whiting AL;Aguilar-Alonso F;Takagi K;Walinda E;Sasaki Y;Shimokawa T;Mizushima T;Ohki I;Ariyoshi M;Tochio H;Bernal F;Shirakawa M;Iwai K
通讯作者：
Iwai K
影响因子：
16
作者：
Elliott, Paul R.;Leske, Derek;Hrdinka, Matous;Bagola, Katrin;Fiil, Berthe K.;McLaughlin, Stephen H.;Wagstaff, Jane;Volkmar, Norbert;Christianson, John C.;Kessler, Benedikt M.;Freund, Stefan M. V.;Komander, David;Gyrd-Hansen, Mads
通讯作者：
Gyrd-Hansen, Mads
影响因子：
9.9
作者：
Eraslan, Basak;Wang, Dongxue;Gagneur, Julien
通讯作者：
Gagneur, Julien
影响因子：
64.8
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
通讯作者：
Harper JW