Stochastic Modeling of Post-Transcriptional Regulation of Gene Expression in Bacteria

在这个项目中，PI将开发定量随机模型，用于通过转录后调节调节基因表达，使用分析方法和随机模拟相结合。具体目标是：1）开发一个分析框架，用于对基因表达中的内在噪声进行建模，重点关注蛋白质的转录后调控。2)开发小RNA对基因表达的转录后调控的分析和计算模型。3)通过群体感应（QS）和碳储存调节因子（CsrA）途径模拟基因表达的转录后调节。该项目将为解释和分析基因表达随机效应实验的理论框架提供几个重要结果。所获得的精确结果将把mRNA和蛋白质分布与基因表达的一般模型联系起来。拟议研究的跨学科方面将导致生物学研究的重要进展。建议的QS和CsrA调控网络的建模将提供重要的洞察这些途径的基因表达的协调和共调节。在更广泛的层面上，拟议的研究将有助于定量了解细胞通路，其中转录后调控起着至关重要的作用。该项目将涉及指导物理学和生物学学生进行生物系统的跨学科研究。除了培训研究生和本科生进行研究，拟议的工作将现代化的生物物理学现有课程与当前的研究成果整合到课程。在拟议的工作过程中开发的所有课程材料和计算机程序将通过网络界面免费提供给科学界，从而加快发现的步伐。在拟议的研究过程中获得的结果将是指导旨在控制QS和CsrA途径的策略的重要投入。

In this project the PI will develop quantitative stochastic models for modulation of gene expression by post-transcriptional regulation using a combination of analytical approach and stochastic simulations. The specific aims are to: 1) Develop an analytical framework for modeling intrinsic noise in gene expression focusing on post-transcriptional regulation by proteins. 2) Develop analytical and computational models for post-transcriptional regulation of gene expression by small RNAs. 3) Model post-transcriptional regulation of gene expression by the quorum sensing (QS) and carbon storage regulator (CsrA) pathways. The project will contribute several significant results to the theoretical framework for interpretation and analysis of experiments focusing on stochastic effects in gene expression. The exact results obtained will connect mRNA and protein distributions with general models of gene expression. The interdisciplinary aspects of the proposed research will lead to important advances in biological research. The proposed modeling of the QS and the CsrA regulatory networks will provide important insight into coordination and coregulation of gene expression by these pathways. At a broader level, the proposed research will contribute to a quantitative understanding of cellular pathways in which posttranscriptional regulation plays a critical role. The project will involve mentoring physics and biology students in interdisciplinary research on biological systems. In addition to training the graduate and undergraduate students performing the research, the proposed work will modernize an existing course in biological physics with the integration of results from current research into the coursework. All course material and computer programs developed during the course of the proposed work will be made freely available to the scientific community via Web interfaces thereby accelerating the pace of discovery. The results obtained during the course of the proposed research will be important inputs in guiding strategies aimed at controlling the QS and CsrA pathways.