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

在这个项目中，PI将利用分析方法和随机模拟相结合的方法，开发转录后调控基因表达的定量随机模型。其具体目的是：1)开发一个分析框架，用于模拟基因表达中的内在噪声，重点是蛋白质转录后调控。2)建立小RNA转录后调控基因表达的分析和计算模型。3)通过群体感应(QS)和碳库调节(CSRA)途径模拟基因表达的转录后调控。该项目将为解释和分析侧重于基因表达中随机效应的实验的理论框架贡献几个重要的结果。得到的准确结果将把信使核糖核酸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。对QS和CSRA调控网络的拟议建模将为通过这些途径协调和共同调节基因表达提供重要的见解。在更广泛的层面上，这项拟议的研究将有助于对转录后调控发挥关键作用的细胞途径的定量理解。该项目将指导物理学和生物学专业的学生进行生物系统的跨学科研究。除了培训进行研究的研究生和本科生外，拟议的工作还将使现有的一门生物物理课程现代化，将当前研究的结果整合到课程工作中。在拟议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旨在控制QS和CSRA途径的指导战略的重要投入。

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.