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

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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.