Using Microfluidic Affinity Analysis to Probe Transcriptional Regulation

使用微流控亲和力分析来探测转录调控

• 批准号: 9011088
• 负责人: Polly Morrell Fordyce
• 金额: $ 24.9万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2017-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9011088
• 关键词: Achievement; Address; Affect; Affinity; Award; Behavior; Binding; Biological Sciences; Biology; Biotechnology; Boxing; Cell physiology; Cells; Code; Collaborations; Complex; DNA; DNA Sequence; DNA-Binding Proteins; Data; Development; Disease; Ensure; Evolution; Functional disorder; Funding; Gene Expression; Gene Expression Regulation; Genes; Genetic Code; Genetic Polymorphism; Genetic Transcription; Genomics; Glucocorticoid Receptor; Goals; Human Genome; Human Genome Project; Immunoprecipitation; In Vitro; Individual; Instruction; Laboratories; Lead; Libraries; Ligands; Location; Maps; Measurement; Measures; Microfluidics; Modeling; Nucleosomes; Oligonucleotides; Organ; Organism; Pattern; Proteins; Public Health; Recruitment Activity; Regulation; Regulator Genes; Regulatory Element; Resources; Role; Signal Transduction; Specific qualifier value; Specificity; Stereotyping; System; Thermodynamics; Time; Tissues; Training; Transcriptional Regulation; Transgenes; Universities; Variant; Work; base; career; cell type; design; gene therapy; genome-wide; human disease; human genome sequencing; improved; in vivo; model building; novel; preference; programs; reconstruction; research study; response; success; synthetic biology; targeted sequencing; transcription factor

DESCRIPTION (provided by applicant): In a watershed achievement, the Human Genome Project (HGP) recently sequenced the entire human genome, providing a wealth of information about potential genes and regulatory sequences. Despite this success, exactly how genomic sequence specifies the behavior and development of complex organisms remains largely unknown. Gene expression within cells is tightly regulated, with many genes expressed only under certain environmental conditions or at stereotyped time points during development. The next great challenge lies in developing a mechanistic understanding of how regulatory sequences dictate gene expression, with the ultimate goal of being able to quantitatively predict expression levels from sequence. Solving this challenge would have far-reaching impacts in biology, elucidating how changes in regulatory sequence can lead to transcriptional dysfunction and disease and improving rational design of transgenes for gene therapy. Regulation of gene expression is accomplished primarily via binding of transcription factors at specific genomic loci. Once bound, transcription factors can either recruit or block the general transcription machinery, thereby activating or repressing transcription. Most leading models of transcriptional regulation are built upon thermodynamic principles, and require information about transcription factor concentrations in vivo and their affinities for different DNA sequences. Despite this central role for binding affinities, experiments to date have been forced to infer affinities from genome-wide occupancy and expression measurements due to a lack of biophysical data. Using a recently developed microfluidic system that permits the high-throughput measurement of interaction affinities, this proposal seeks to systematically investigate the thermodynamics of transcriptional regulation at multiple scales, from individual interactions between transcription factors and target sequences to the nucleation of assemblies of DNA binding proteins at regulatory loci. Experiments will focus on, in turn: (1) how particular contacts between protein residues and DNA bases determine interaction affinities; (2) how cell-specific signals modify these interactions to dictate tissue-specific expression patterns; (3) how evolutionary changes in both regulatory DNA sequences and transcription factors rewire transcriptional networks during evolution to drive phenotypic change; and (4) how cooperativity and competition between transcription factors affect binding patterns to influence gene expression. Data from these experiments will provide crucial information required to construct ground-up, quantitative models of transcriptional regulation and increase our ability to predict gene expression from regulatory sequence. The funding provided by this K99 award would provide crucial resources for the PI, Polly Fordyce, to receive 2 years of additional formal training in the biological sciences and ensure a successful transition to an independent career.

描述（由申请人提供）：人类基因组计划（HGP）最近对整个人类基因组进行了测序，提供了有关潜在基因和调控序列的大量信息，这是一项里程碑式的成就。尽管取得了这一成功，但基因组序列究竟如何指定复杂生物体的行为和发育仍然很大程度上未知。细胞内的基因表达受到严格调控，许多基因仅在某些环境条件下或在发育过程中的固定时间点表达。下一个巨大的挑战在于建立对调控序列如何决定基因表达的机制理解，最终目标是能够根据序列定量预测表达水平。解决这一挑战将对生物学产生深远的影响，阐明调控序列的变化如何导致转录功能障碍和疾病，并改进基因治疗转基因的合理设计。基因表达的调节主要通过转录因子在特定基因组位点的结合来完成。 一旦结合，转录因子可以招募或阻断一般转录机制，从而激活或抑制转录。大多数领先的转录调控模型都是建立在热力学原理的基础上，需要有关体内转录因子浓度及其对不同 DNA 序列的亲和力的信息。尽管结合亲和力发挥着核心作用，但由于缺乏生物物理数据，迄今为止的实验被迫从全基因组占用和表达测量中推断亲和力。该提案利用最近开发的微流体系统，可以高通量测量相互作用亲和力，旨在系统地研究转录的热力学 多尺度的调控，从转录因子和靶序列之间的个体相互作用到调控位点处 DNA 结合蛋白组装的成核。实验将依次关注：（1）蛋白质残基和 DNA 碱基之间的特定接触如何决定相互作用亲和力； (2)细胞特异性信号如何改变这些相互作用以决定组织特异性表达模式； (3) 调控DNA序列和转录因子的进化变化如何在进化过程中重新连接转录网络以驱动表型变化； (4)转录因子之间的合作和竞争如何影响结合模式从而影响基因表达。这些实验的数据将提供构建转录调控的基础定量模型所需的关键信息，并提高我们根据调控序列预测基因表达的能力。 K99 奖项提供的资金将为 PI Polly Fordyce 提供重要资源，让其接受 2 年额外的生物科学正式培训，并确保成功过渡到独立职业。