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Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions

机译:对蛋白酪氨酸磷酸化位点乐百氏共同监管揭示了新的蛋白质相互作用

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摘要

Cell signaling networks propagate information from extracellular cues via dynamic modulation of protein–protein interactions in a context-dependent manner. Networks based on receptor tyrosine kinases (RTKs), for example, phosphorylate intracellular proteins in response to extracellular ligands, resulting in dynamic protein–protein interactions that drive phenotypic changes. Most commonly used methods for discovering these protein–protein interactions, however, are optimized for detecting stable, longer-lived complexes, rather than the type of transient interactions that are essential components of dynamic signaling networks such as those mediated by RTKs. Substrate phosphorylation downstream of RTK activation modifies substrate activity and induces phospho-specific binding interactions, resulting in the formation of large transient macromolecular signaling complexes. Since protein complex formation should follow the trajectory of events that drive it, we reasoned that mining phosphoproteomic datasets for highly similar dynamic behavior of measured phosphorylation sites on different proteins could be used to predict novel, transient protein–protein interactions that had not been previously identified. We applied this method to explore signaling events downstream of EGFR stimulation. Our computational analysis of robustly co-regulated phosphorylation sites, based on multiple clustering analysis of quantitative time-resolved mass-spectrometry phosphoproteomic data, not only identified known sitewise-specific recruitment of proteins to EGFR, but also predicted novel, a priori interactions. A particularly intriguing prediction of EGFR interaction with the cytoskeleton-associated protein PDLIM1 was verified within cells using co-immunoprecipitation and in situ proximity ligation assays. Our approach thus offers a new way to discover protein–protein interactions in a dynamic context- and phosphorylation site-specific manner.
机译:细胞信号网络通过动态调节蛋白质间相互作用来从细胞外信号中传播信息。例如,基于受体酪氨酸激酶(RTK)的网络会响应细胞外配体而磷酸化细胞内蛋白质,从而导致驱动表型变化的动态蛋白质间相互作用。然而,发现蛋白质间相互作用的最常用方法是优化用于检测稳定,寿命更长的复合物,而不是动态信号网络的基本组成部分(如RTK介导的那些)瞬时相互作用的类型。 RTK激活下游的底物磷酸化修饰底物活性并诱导磷酸特异性结合相互作用,导致形成大的瞬时大分子信号复合物。由于蛋白质复合物的形成应遵循推动它发生的事件的轨迹,因此我们认为,挖掘蛋白质组学数据集以获得不同蛋白质上测得的磷酸化位点高度相似的动态行为,可以用于预测以前未发现的新型,瞬时蛋白质-蛋白质相互作用。我们应用这种方法来探索EGFR刺激下游的信号传导事件。我们基于定量时间分辨质谱磷酸化蛋白质组学数据的多聚类分析对鲁棒共调节的磷酸化位点进行了计算分析,不仅确定了蛋白质向EGFR的已知位点特异性募集,而且还预测了新的先验相互作用。使用共免疫沉淀和原位邻近连接测定法,在细胞内证实了EGFR与细胞骨架相关蛋白PDLIM1相互作用的特别有趣的预测。因此,我们的方法提供了一种以动态背景和磷酸化位点特异性方式发现蛋白质-蛋白质相互作用的新方法。

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