Uncovering the fundamental principles of transcriptional regulation

揭示转录调控的基本原理

• 批准号: 9751337
• 负责人: Robert Charles Brewster
• 金额: $ 41.88万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9751337
• 关键词: Animal Model; Binding; Binding Sites; Cells; Code; Complex; DNA; Decision Making; Disease; Dissection; Escherichia coli; Feedback; Foundations; Gene Expression; Gene Expression Regulation; Genes; Genome; Individual; Investigation; Location; Measures; Methods; Nucleic Acid Regulatory Sequences; Pattern; Play; Process; Proteins; Regulation; Regulatory Element; Role; Scheme; Specific qualifier value; Stimulus; Theoretical model; Time; Transcriptional Regulation; Work; base; biophysical model; design; experimental study; fitness; genomic data; recruit; response; synthetic biology; transcription factor

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.

项目摘要/摘要 刻在DNA中的调节代码指出了如何通过转录调节基因的表达 响应环境或细胞内刺激的因素（TF）。此代码设置了每个基因的方式 通过控制TF何时何地结合对刺激的反应。在我的实验室中，我们的工作致力于开发 对基因表达的预测理解。这是通过数量之间的紧密相互作用来实现的 基于详细的生物物理模型的具有理论预测，以及一种实验方法。 对系统扰动的定量结果的伪造预测应用于合成目标 基因。我的实验室中使用大肠杆菌作为模型生物的工作，重点是两个人的系统解剖 调节结合位点在基因表达中的不同作用： 单个局部“顺式调节”结合位点的调节作用。 非本地，竞争结合位点的调节作用散布在整个基因组中。 为了表征本地，顺式调节性相互作用，我们使用合成生物学方法系统地测量 每个TF的调节功能是其在基因上结合的位置以及其结合的序列的函数。 通过此过程，我们将在没有基因特异性因素的情况下发现每个TF的孤立功能 （例如反馈和TF-TF相互作用）在基因组数据中阻塞了这些基本信息。研究角色 在竞争绑定位点，我们使用相同的合成生物学方法来控制 TF结合位点，以测量TFS竞争如何控制基因表达中的空间和临时模式。 综上所述，这些投资方向旨在提供有关法规的完整图片 单个基因的水平。这些方法不是正交的，很难研究一种而不欣赏 另一个；为了量化竞争如何改变表达方式，我们必须了解对 单独行动并研究当地监管要素，我们必须了解影响 基因组周围不可避免的，自然发生的竞争结合位点。我们的方法是设计的 分离和量化这些调节效应，以提供预测表达所需的基础 在天然基因中观察到的复杂调节方案。 在接下来的5年中，我们将证明，通过基于绑定位置来表征单个TF功能 和序列，我们可以将基因特征特征的作用从基本的TF函数中删除，以使 这些成分如何在自然发生的基因中看到的复杂调节区域起作用。 此外，我们将开发一个理论模型，以说明TF竞争在精心策划中的作用 空间和时间的表达模式对于细胞决策和拟合度至关重要。