Landman Jasper, Brewster Robert C, Weinert Franz M, Phillips Rob, Kegel Willem K
Van 't Hoff Laboratory for Physical & Colloid Chemistry, Utrecht University, Utrecht, the Netherlands.
European Synchrotron Radiation Facility, Grenoble, France.
PLoS One. 2017 Jul 7;12(7):e0179235. doi: 10.1371/journal.pone.0179235. eCollection 2017.
Individual regulatory proteins are typically charged with the simultaneous regulation of a battery of different genes. As a result, when one of these proteins is limiting, competitive effects have a significant impact on the transcriptional response of the regulated genes. Here we present a general framework for the analysis of any generic regulatory architecture that accounts for the competitive effects of the regulatory environment by isolating these effects into an effective concentration parameter. These predictions are formulated using the grand-canonical ensemble of statistical mechanics and the fold-change in gene expression is predicted as a function of the number of transcription factors, the strength of interactions between the transcription factors and their DNA binding sites, and the effective concentration of the transcription factor. The effective concentration is set by the transcription factor interactions with competing binding sites within the cell and is determined self-consistently. Using this approach, we analyze regulatory architectures in the grand-canonical ensemble ranging from simple repression and simple activation to scenarios that include repression mediated by DNA looping of distal regulatory sites. It is demonstrated that all the canonical expressions previously derived in the case of an isolated, non-competing gene, can be generalised by a simple substitution to their grand canonical counterpart, which allows for simple intuitive incorporation of the influence of multiple competing transcription factor binding sites. As an example of the strength of this approach, we build on these results to present an analytical description of transcriptional regulation of the lac operon.
单个调节蛋白通常负责同时调节一系列不同的基因。因此,当这些蛋白中的一种受到限制时,竞争效应会对受调节基因的转录反应产生重大影响。在此,我们提出了一个通用框架,用于分析任何通用的调节结构,该框架通过将这些效应分离到一个有效浓度参数中来考虑调节环境的竞争效应。这些预测是使用统计力学的巨正则系综来制定的,基因表达的倍数变化被预测为转录因子数量、转录因子与其DNA结合位点之间相互作用强度以及转录因子有效浓度的函数。有效浓度由转录因子与细胞内竞争结合位点的相互作用设定,并通过自洽确定。使用这种方法,我们分析了巨正则系综中的调节结构,范围从简单的抑制和简单的激活到包括由远端调节位点的DNA环化介导的抑制等情况。结果表明,先前在孤立的、非竞争基因情况下推导的所有规范表达式,都可以通过简单替换为其巨正则对应物来进行推广,这允许简单直观地纳入多个竞争转录因子结合位点的影响。作为这种方法强大之处的一个例子,我们基于这些结果给出了乳糖操纵子转录调控的分析描述。