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

基本信息

批准号：
9196360
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
项目类别：
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/9196360
关键词：
Achievement Address Affect Affinity Amino Acid Sequence Award Behavior Binding Binding Proteins Biological Sciences Biology Biophysics Biotechnology 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 Phenotype 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 experimental study gene therapy genome-wide human disease improved in vivo novel preference programs reconstruction response success synthetic biology transcription factor virtual

项目摘要

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）：在分水岭成就中，人类基因组项目（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节序列的大量信息。尽管取得了成功，但基因组序列的准确指定复杂生物的行为和发展仍然很大程度上是未知的。细胞内的基因表达受到严格调节，许多基因仅在某些环境条件下或在发育过程中定型的时间点表达。下一个巨大的挑战在于对调节序列如何决定基因表达的机械理解，其最终目标是能够从序列中定量预测表达水平。解决这一挑战将对生物学产生深远的影响，阐明调节序列的变化如何导致转录功能障碍和疾病，并改善基因治疗的转基因的合理设计。基因表达的调节主要是通过特定基因组基因座的转录因子的结合来完成的。一旦结束，转录因子就可以募集或阻止一般的转录机械，从而激活或抑制转录。大多数转录调控的主要模型都是基于热力学原理的，并且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。尽管在结合亲和力方面具有核心作用，但由于缺乏生物物理数据，迄今为止，实验已被迫从全基因组占用和表达测量中推断出亲和力。使用最近开发的微流体系统，该系统允许对相互作用亲和力进行高通量测量，该建议旨在系统地研究转录的热力学从多个尺度的调节，从转录因子和靶序列之间的单个相互作用到调节基因座DNA结合蛋白组件的成核。实验将重点关注：（1）蛋白质残基和DNA碱基之间的特定接触如何确定相互作用亲和力；（2）细胞特异性信号如何修改这些相互作用以决定组织特异性表达模式；（3）在进化过程中，调节性DNA序列和转录因子的进化变化如何驱动表型变化；（4）转录因子之间的合作和竞争如何影响结合模式以影响基因表达。这些实验的数据将提供构建基础，转录调控的定量模型所需的关键信息，并提高我们从调节序列中预测基因表达的能力。该K99奖提供的资金将为PI Polly Fordyce提供重要的资源，以在生物科学领域接受2年的额外正式培训，并确保成功过渡到独立职业。