Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.
Department of Physics, California Institute of Technology, Pasadena, California, United States of America.
PLoS Comput Biol. 2019 Feb 4;15(2):e1006226. doi: 10.1371/journal.pcbi.1006226. eCollection 2019 Feb.
Despite the central importance of transcriptional regulation in biology, it has proven difficult to determine the regulatory mechanisms of individual genes, let alone entire gene networks. It is particularly difficult to decipher the biophysical mechanisms of transcriptional regulation in living cells and determine the energetic properties of binding sites for transcription factors and RNA polymerase. In this work, we present a strategy for dissecting transcriptional regulatory sequences using in vivo methods (massively parallel reporter assays) to formulate quantitative models that map a transcription factor binding site's DNA sequence to transcription factor-DNA binding energy. We use these models to predict the binding energies of transcription factor binding sites to within 1 kBT of their measured values. We further explore how such a sequence-energy mapping relates to the mechanisms of trancriptional regulation in various promoter contexts. Specifically, we show that our models can be used to design specific induction responses, analyze the effects of amino acid mutations on DNA sequence preference, and determine how regulatory context affects a transcription factor's sequence specificity.
尽管转录调控在生物学中具有核心重要性,但确定单个基因的调控机制,更不用说整个基因网络的调控机制了,这一直是具有挑战性的。在活细胞中破译转录调控的生物物理机制并确定转录因子和 RNA 聚合酶结合位点的能量特性尤其具有挑战性。在这项工作中,我们提出了一种使用体内方法(大规模平行报告基因分析)来剖析转录调控序列的策略,以制定定量模型,将转录因子结合位点的 DNA 序列映射到转录因子-DNA 结合能。我们使用这些模型将转录因子结合位点的结合能预测到与其实测值相差 1kBT 以内。我们进一步探讨了这种序列-能量映射与各种启动子背景下转录调控机制的关系。具体来说,我们表明我们的模型可用于设计特定的诱导反应,分析氨基酸突变对 DNA 序列偏好的影响,并确定调控环境如何影响转录因子的序列特异性。