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

在这个项目中，PI将使用分析方法和随机模拟相结合的方法，开发通过转录后调控调节基因表达的定量随机模型。具体目标是：1)建立一个分析框架来模拟基因表达中的内在噪声，重点关注蛋白质的转录后调控。2)建立小rna转录后调控基因表达的分析和计算模型。3)模拟群体感应（quorum sensing， QS）和碳储存调节（carbon storage regulator, CsrA）途径对基因表达的转录后调控。该项目将为解释和分析基因表达随机效应的实验提供一些重要的理论框架。获得的精确结果将把mRNA和蛋白质的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。提出的QS和CsrA调控网络的建模将为这些途径的基因表达协调和协同调控提供重要的见解。在更广泛的层面上，拟议的研究将有助于定量理解细胞通路，其中转录后调控起着关键作用。该项目将包括指导物理学和生物学学生进行生物系统的跨学科研究。除了训练进行研究的研究生和本科生外，拟议的工作将使现有的生物物理学课程现代化，将当前的研究成果整合到课程中。所有的课程材料和在计划工作过程中开发的计算机程序将通过网络接口免费提供给科学界，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通路的策略的重要输入。

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.