Strome Bob, Hsu Ian Shenyen, Li Cheong Man Mitchell, Zarin Taraneh, Nguyen Ba Alex, Moses Alan M
Department of Cell & Systems Biology, University of Toronto, 25 Willcocks Street, Toronto, ON, M5S 3B2, Canada.
Center for Analysis of Genome Evolution and Function, 25 Willcocks Street, Toronto, ON, M5S 3B2, Canada.
BMC Syst Biol. 2018 Jul 3;12(1):75. doi: 10.1186/s12918-018-0597-3.
The effort to characterize intrinsically disordered regions of signaling proteins is rapidly expanding. An important class of disordered interaction modules are ubiquitous and functionally diverse elements known as short linear motifs (SLiMs).
To further examine the role of SLiMs in signal transduction, we used a previously devised bioinformatics method to predict evolutionarily conserved SLiMs within a well-characterized pathway in S. cerevisiae. Using a single cell, reporter-based flow cytometry assay in conjunction with a fluorescent reporter driven by a pathway-specific promoter, we quantitatively assessed pathway output via systematic deletions of individual motifs. We found that, when deleted, 34% (10/29) of predicted SLiMs displayed a significant decrease in pathway output, providing evidence that these motifs play a role in signal transduction. Assuming that mutations in SLiMs have quantitative effects on mechanisms of signaling, we show that perturbations of parameters in a previously published stochastic model of HOG signaling could reproduce the quantitative effects of 4 out of 7 mutations in previously unknown SLiMs.
Our study suggests that, even in well-characterized pathways, large numbers of functional elements remain undiscovered, and that challenges remain for application of systems biology models to interpret the effects of mutations in signaling pathways.
对信号蛋白内在无序区域进行特征描述的工作正在迅速扩展。一类重要的无序相互作用模块是普遍存在且功能多样的元件,称为短线性基序(SLiMs)。
为了进一步研究SLiMs在信号转导中的作用,我们使用了先前设计的生物信息学方法来预测酿酒酵母中一个特征明确的信号通路内进化保守的SLiMs。通过单细胞、基于报告基因的流式细胞术检测,并结合由通路特异性启动子驱动的荧光报告基因,我们通过系统删除单个基序来定量评估通路输出。我们发现,当被删除时,34%(29个中的10个)预测的SLiMs显示通路输出显著降低,这证明这些基序在信号转导中起作用。假设SLiMs中的突变对信号传导机制有定量影响,我们表明,在先前发表的HOG信号传导随机模型中对参数的扰动可以重现7个先前未知的SLiMs中4个突变的定量影响。
我们的研究表明,即使在特征明确的信号通路中,仍有大量功能元件未被发现,并且将系统生物学模型应用于解释信号通路中突变的影响仍然存在挑战。