Quantitative Modeling of Signal Transduction in Bacterial Chemotaxis

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DESCRIPTION (provided by applicant): The long term goal of this research project is to achieve quantitative, systems level understanding of the signal transduction pathway in E. coli chemotaxis. We want to integrate the knowledge on the E. coli chemotaxis signaling pathway over different (length and time) scales into a mathematical description (model) of the system that can be used to explain and predict quantitatively the E. coli chemotaxis response to any given temporal and spatial signal (stimulus). The models will be constructed based on known molecular details of the signaling pathway and at the appropriate resolution comparable to experimental data. These models will be studied by using statistical physics methods, Monte Carlo simulation and dynamical systems analysis. The results from these models will be used to explain existing data, make testable predictions and the comparison with experimental data will feed back to improve/refine the models. In this proposal, we will focus on two essential aspects of the E. coli chemotaxis pathway: 1) Signal amplification in the (fast) kinase response. We are interested in finding out the structural basis for the observed signal amplification, e.g., how many receptors each cooperative functional complex contains. We want to understand the molecular mechanism for the wide dynamic range of high sensitivity observed in E. coli chemotaxis. We want to understand how cell achieve these excellent properties (high gain, high sensitivity over a wide range of backgrounds) with variable (noisy) internal components. 2) Kinetics of the (slower) adaptation process. We want to understand the adaptation kinetics quantitatively, e.g., how fast the system adapts and how the adaptation time depends on the external stimulus strength. We want to understand the adaptation kinetics to time varying stimulus, such as exponential ramps with different ramp rates. Eventually, we want to be able to model and predict the signaling pathway dynamics as the cell moves in its natural environment. The concepts and tools developed in the quantitative, systems level modeling of a complete sensory signal transduction pathway will be useful in understanding signaling pathways and sensory systems in higher organisms, including human. The molecular level understanding of the bacterial chemotaxis pathway is important to study the role of bacterial pathogens in human health.