Systematic identification of changes in the yeast protein interaction network in response to environmental, chemical, and genetic perturbation [interactome data]

To understand the principles underlying protein-protein interaction (PPI) complex changes in response to external perturbations, we created a highly multiplexed version of the murine dihydrofolate reductase protein complementation assay (mDHFR PCA) in Saccharomyces cerevisiae, allowing quantitative PPI complex profiling in vivo. We investigated the effects of 14 different conditions (including small molecules, abiotic stress factors, and nutrient composition) on a total of 1383 PPIs. More than half of PPIs (758) were found to be variable, and their Gene Ontology (GO) annotations were found to be informative of both the nature of the perturbation within each condition, as well as the overall variability of the interactions across conditions. Many perturbations triggered network changes characterized by large connected modules centered around highly connected proteins ('hubs'), suggesting that cellular control of a few proteins (e.g., by mRNA levels) can induce widespread PPI remodeling. Under a diauxic shift from glucose to ethanol as the main carbon source, we found a striking relationship between PPI changes measured by our assay and those predicted by mRNA expression under a simple law of mass action based model.为解析蛋白质-蛋白质相互作用（protein-protein interaction, PPI）复合物响应外界扰动的内在原理，我们在酿酒酵母（Saccharomyces cerevisiae）中构建了一种高度多重化的鼠源二氢叶酸还原酶蛋白质互补测定法（murine dihydrofolate reductase protein complementation assay, mDHFR PCA），可实现体内PPI复合物的定量谱分析。我们共考察了14种不同处理条件（涵盖小分子、非生物胁迫因子及营养组分）对总计1383组PPI的影响。研究发现，超过半数的PPI（758组）呈现动态变化，其基因本体（Gene Ontology, GO）注释不仅能够反映各处理条件下扰动的本质特征，还可体现不同条件间相互作用的整体变异模式。诸多扰动引发的相互作用网络变化，均以围绕高度连接蛋白（即“枢纽蛋白”）的大型连接模块为典型特征，这表明仅通过调控少数蛋白质的表达（例如通过mRNA水平），即可诱导广泛的PPI重塑。在以葡萄糖为主要碳源向乙醇转换的二次生长转换过程中，我们发现，本测定法测得的PPI变化与基于简单质量作用定律模型预测的mRNA表达变化之间存在显著关联。