Binding Kinetics in Transcription Activation and Repression

转录激活和抑制中的结合动力学

• 批准号: 10638937
• 负责人: Timothee Lionnet
• 金额: $ 63.06万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-06 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10638937
• 关键词: Address; Adopted; Affinity; Architecture; Binding; Biological Assay; Biotechnology; Cells; Chromatin; Code; Complex; DNA; DNA Binding; DNA Binding Domain; DNA Sequence; DNA-Protein Interaction; Data; Disease; Engineering; Environment; Event; Exhibits; Genes; Genetic Determinism; Genetic Transcription; Genome; Goals; Health; Human; Kinetics; Link; Maps; Measures; Microscopy; Modeling; Mutation; Nuclear; Output; Property; Proteins; Repression; Sampling; Scanning; Site; Specific qualifier value; Specificity; Synthetic Genes; Time; Transcriptional Activation; Transcriptional Regulation; Variant; Vertebral column; Visualization; Zinc Fingers; base; design; experimental study; gene repression; genetic variant; imaging approach; imaging platform; in vitro Assay; inorganic phosphate; interest; large scale data; model design; novel; programs; protein protein interaction; reconstitution; recruit; residence; single molecule; sound; trait; transcription factor; trend

Transcription regulation is a key determinant of how genetic variability is interpreted by a cell: more than 90% of traits- and disease-associated genetic variants map outside of the coding genome. While we now have a robust understanding of where human TFs might bind, enabling predictions of TF binding when data is unavailable, those approaches do not tell us how frequently a TF binds, how long it stays bound, and what it does once bound, which makes it difficult to predict the impact that TF or regulatory site variants will have on transcription. Critical regulatory architectures, primarily studied with activators, typically favor transient, lower affinity interactions between regulators and the DNA over stronger ones. This is consistent with observations that the transcription machinery can load very efficiently, within seconds. Whether similar strategies are adopted by repressors is unclear, given the much longer timescales over which repression unfolds. In this proposal, we will build upon a novel AI-based Zinc Finger design model to engineer synthetic mimics of endogenous DNA binding domains that bind arbitrary sequences with tunable affinity and measure their binding kinetics in reconstituted assays. We will deploy cutting-edge single-molecule tracking microscopy in order to measure the binding kinetics of these domains to their targets and at non-specific site inside living cells. These experiments will enable reconstructing the strategies deployed by Transcription Factors to find their targets in the genome haystack. We will fuse these DNA binding domains with activating or repressing domains in order to directly link Transcription Factor binding kinetics to the timing and output of transcription bursts synthesized by their target genes. Together, these data will provide mechanistic access to the strategies that repressors and activators have evolved to find and regulate their targets. The results constitute key design principles for novel biotechnologies based on Transcription Factor reprogramming.

转录调控是细胞如何解释遗传变异的关键决定因素：超过 90% 与性状和疾病相关的遗传变异图谱位于编码基因组之外。虽然我们现在有一个 对人类 TF 可能结合的位置有深入的了解，从而能够在数据存在时预测 TF 结合 由于不可用，这些方法并没有告诉我们 TF 结合的频率、保持结合的时间以及它的作用。 一旦结合就会发生，这使得很难预测 TF 或调控位点变体将对 转录。 主要用激活剂进行研究的关键调控架构通常有利于瞬时的、较低亲和力的 调节因子和 DNA 之间的相互作用强于更强的相互作用。这与观察结果一致 转录机器可以在几秒钟内非常有效地加载。是否采取类似策略 鉴于镇压展开的时间尺度要长得多，镇压因素尚不清楚。 在本提案中，我们将基于一种新颖的基于人工智能的锌指设计模型来设计合成模拟物 内源 DNA 结合域，以可调节的亲和力结合任意序列并测量其 重构测定中的结合动力学。我们将在以下领域部署尖端的单分子跟踪显微镜 为了测量这些结构域与其目标以及生物体内非特定位点的结合动力学 细胞。这些实验将能够重建转录因子部署的策略，以发现 他们的目标在基因组大海捞针中。 我们将这些 DNA 结合域与激活或抑制域融合，以便直接连接 转录因子结合动力学对其靶标合成的转录爆发的时间和输出的影响 基因。总之，这些数据将为阻遏物和激活物的策略提供机械途径。 已经进化到寻找和调节它们的目标。结果构成了新颖的关键设计原则 基于转录因子重编程的生物技术。