Modeling and Analysis of Bacterial Signaling Circuits

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DESCRIPTION (provided by applicant): Two-component systems are one of the major modes of signal transduction in bacteria. They provide an excellent class of circuits for exploring, through mathematical modeling and experiments, many of the basic design principles underlying cell signaling. The long-term objectives of the research in this proposal are to develop and test mathematical models for the network of two-component systems in E. coli. The research in this proposal will build on previous work in which we have formulated a mathematical model for some of the simplest examples of two-component signaling and have developed a number of new experimental tools for studying these systems. The research will combine mathematical modeling with experimental tests that make use of genetics and fluorescence microscopy to follow various steps in the signaling process in live cells. The specific aims of this proposal are to: 1) Analyze the dynamics of the phosphorylation cycle in two- component signaling and properties of the circuit at steady state; 2) Analyze the role of positive autoregulation in two-component signaling to determine its effects on the steady-state and dynamic properties of the circuit and test the predictions using the PhoQ/PhoP two-component system; 3) Develop and test models for response regulator binding to DNA in vivo to infer the functional relation between the fraction of bound response regulator and transcriptional activity; 4) Develop and test a model of weak crosstalk from a separate two-component system and from other phosphodonors to test the hypothesis that the phosphorylation cycle and stoichiometry of regulatory proteins are important for crosstalk suppression. Many two-component signaling systems play important roles in pathogenesis. These include circuits that regulate the expression of virulence determinants as well as more general stress-responsive or antibiotic resistance systems that are necessary for the survival of pathogens. An improved understanding of the structure of these circuits and useful models to understand the effects of circuit perturbations will likely contribute to our understanding of virulence and survival of pathogens and aid in the development of novel antimicrobials.