Using Microfluidic Affinity Analysis to Probe Transcriptional Regulation

描述（由申请人提供）：人类基因组计划（HGP）最近完成了整个人类基因组的测序，为潜在基因和调控序列提供了丰富的信息，这是一项分水岭式的成就。尽管取得了这一成功，但基因组序列究竟是如何指定复杂生物体的行为和发育的，在很大程度上仍然是未知的。细胞内的基因表达受到严格调控，许多基因仅在特定的环境条件下或在发育过程中固定的时间点表达。下一个巨大的挑战在于发展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，阐明调控序列的变化如何导致转录功能障碍和疾病，并改善基因治疗转基因的合理设计。基因表达的调控主要是通过特定基因组位点上转录因子的结合来完成的。

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.