Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology.
Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology.
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DOI：
10.1016/j.cels.2023.02.003
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发表时间：
2023-04-19
期刊：
影响因子：
9.3
通讯作者：
中科院分区：
文献类型：
--
作者：
转录因子（TF）控制基因表达，通常协同作用。经典的热力学模型提供了一个生物物理解释的基础上结合协同性和RNA聚合酶的调节招聘的协同作用。由于转录需要聚合酶通过多种状态转换，最近的工作表明，“动力学协同作用”可以通过转录因子作用于转录周期的不同步骤而产生。这些类型的协同作用并不相互排斥，很难从概念上和实验上理清。在这里，我们建模并构建了一个合成电路，其中TF与DNA上的单个共享位点结合，使得TF不能通过同时结合来协同作用。我们将mRNA的产生作为TF结合和转录周期调节的函数进行建模，揭示了依赖于TF浓度、DNA结合亲和力和调节活性的复杂景观。我们使用合成的转录因子，以确认转录周期必须与招聘的定量了解基因调控。Martinez-Corral、Park、Biette等人研究了动力学协同作用，其中转录因子通过功能互补增强彼此的作用。为了消除结合协同性，作者专注于合成的情况下，转录因子结合到一个共享的网站。模型和实验的结合揭示了一个复杂的景观，其中绑定和功能决定协同作用。
Transcription factors (TFs) control gene expression, often acting synergistically. Classical thermodynamic models offer a biophysical explanation for synergy based on binding cooperativity and regulated recruitment of RNA polymerase. Because transcription requires polymerase to transition through multiple states, recent work suggests that “kinetic synergy” can arise through TFs acting on distinct steps of the transcription cycle. These types of synergy are not mutually exclusive and are difficult to disentangle conceptually and experimentally. Here, we model and build a synthetic circuit in which TFs bind to a single shared site on DNA, such that TFs cannot synergize by simultaneous binding. We model mRNA production as a function of both TF binding and regulation of the transcription cycle, revealing a complex landscape dependent on TF concentration, DNA binding affinity, and regulatory activity. We use synthetic TFs to confirm that the transcription cycle must be integrated with recruitment for a quantitative understanding of gene regulation. Martinez-Corral, Park, Biette et al. investigate kinetic synergy in which transcription factors enhance each other’s effect through functional complementarity. To eliminate binding cooperativity, the authors focus on a synthetic scenario where transcription factors bind to a shared site. The combination of modeling and experiments reveals a complex landscape in which binding and function determine synergy.
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