Uncovering the fundamental principles of transcriptional regulation

项目摘要/摘要 Dna中包含的调控密码fi说明了基因的表达如何通过转录调节。 对环境或细胞内刺激作出反应的因子(TF)。这个代码设置了每个单独的基因如何 通过控制TF结合的时间和位置来对刺激做出反应。在我的实验室里，我们的工作致力于开发一种 对基因表达的预测性理解。这是通过量子和量子之间的密切相互作用来实现的。 基于详细生物物理模型的预测性理论预测，以及由 应用于合成靶标的系统摄动定量后果的错误fi预测 吉恩。我的实验室使用大肠杆菌作为模式生物，重点是系统地解剖两个 调控结合位点在基因表达中的不同作用： 个别、局部“顺式调节”结合部位的调节作用。 分散在基因组中的非局部、相互竞争的结合位点的调节作用。 为了表征局部的顺式调控相互作用，我们使用合成生物学方法系统地测量 每个转铁蛋白的调节功能取决于它结合在基因上的什么位置以及它结合到什么序列。 通过这一过程，我们将揭示在缺乏基因特异性fic因子的情况下，每个tf的单独功能。 (如反馈和Tf-Tf相互作用)，在基因组数据中遮挡了这一基本信息。研究其角色 对于竞争结合位点，我们使用同样的合成生物学方法来控制结合位点的数量和强度 Tf结合位点来衡量对Tf的竞争如何控制基因表达的空间和时间模式。 综上所述，这些调查方向旨在提供有关监管的完整图景 单个基因的水平。这些方法不是正交性的，研究一种方法而不加鉴赏是很难的 另一方面，要量化竞争如何改变表达方式，我们必须理解 地方监管要素单独发挥作用，要研究地方监管要素，必须了解其影响 基因组周围不可避免的、自然发生的相互竞争的结合位点。我们的方法是专门设计的 为了分离和量化这些调控效应，以提供预测从 在天然基因中观察到的复杂调控机制。 在接下来的5年里，我们将通过基于结合位置的单个Tf函数来证明这一点 和序列，我们可以把基因特异性fic特征的作用从基本的Tf函数中分离出来，以便更好地理解 在自然产生的基因中，这些成分是如何在复杂的调控区域中共同作用的。 此外，我们将开发一个理论模型，说明TF比赛在编排中的作用 对细胞决策和fi稳定性至关重要的空间和时间表达模式。

Project summary/Abstract The regulatory code, inscribed in DNA, specifies how the expression of a gene will be tuned by transcription factors (TFs) in response to an environmental or intracellular stimulus. This code sets how each individual gene responds to stimuli by controlling when and where TFs bind. In my lab, our work is dedicated to developing a predictive understanding of gene expression. This is accomplished through a close interplay between quanti- tative theoretical predictions based on detailed biophysical models, and an experimental approach guided by falsifiable predictions for the quantitative consequence of systematic perturbation applied to a synthetic target gene. The work in my lab, which uses E. coli as a model organism, focuses on the systematic dissection of two distinct roles of regulatory binding sites in gene expression: The regulatory role of individual, local “cis-regulatory” binding sites. The regulatory role of non-local, competing binding sites scattered throughout the genome. To characterize local, cis-regulatory interactions we use a synthetic biology approach to systematically measure the regulatory function of every TF as a function of where on the gene it binds and to what sequence it binds. Through this process we will uncover the isolated function of each TF in the absence of the gene-specific factors (such as feedback and TF-TF interactions) that occlude this basic information in genomic data. To study the role of competing binding sites, we use this same synthetic biology approach to control the number and strength of TF binding sites to measure how competition for TFs controls spatial and temporal patterns in gene expression. Taken together, these directions of investigation are aimed at providing a complete picture of regulation at the level of a single gene. These methods are not orthogonal, it is difficult to study one without appreciating the other; to quantify how competition alters expression we must understand the “isolated” regulation of the local regulatory elements acting alone, and to study local regulatory elements we must understand the impact of the unavoidable, naturally occurring competing binding sites around the genome. Our approach is designed to isolate and quantify these regulatory effects to provide the foundation required to predict expression from the complex regulatory schemes observed in natural genes. In the next 5 years, we will demonstrate that by characterizing individual TF function based on binding location and sequence, we can disentangle the role of gene-specific features from basic TF function in order to under- stand how these components act together in the complex regulatory regions seen in naturally occurring genes. Furthermore, we will develop a theoretical model that accounts for the role of TF competition in orchestrating expression patterns in space and time that are crucial for cellular decision making and fitness.