Quantitative Modeling of Bacterial Chemotaxis Signaling Pathway

描述（由申请人提供）：本研究项目的长期目标是实现系统级E的定量理解。大肠杆菌的趋化行为及其分子水平的机制。我们将建立基于趋化性信号通路的结构和生化细节的蛋白质相互作用网络及其动力学的数学模型。这些模型将使用解析分析和数值模拟方法进行研究。这些模型的结果将被用来解释实验数据，并作出可检验的预测。模型和实验数据之间的迭代比较将用于改进/细化模型。在本建议中，我们将重点研究E.大肠杆菌趋化途径：1）化学重组阵列的信号动力学和功能。我们将研究混合受体阵列如何区分不同的刺激（信号）以及细胞如何根据信息做出决策。我们想研究ATP水解在传感器激酶信号传导中的作用，以及它如何调节激酶对受体配体结合的反应敏感性。2)鞭毛马达的开关机制及其对机械信号的依赖性。我们想了解鞭毛马达是如何被其机械环境（力、负荷）的变化以及细胞内的化学信号所控制的。总之，我们计划调查和了解如何一个E。大肠杆菌细胞感觉不同的（化学和物理）信号，它如何处理这些信息，以及它如何在复杂的环境中做出决定，多个时变的线索。

DESCRIPTION (provided by applicant): The long term goal of this research project is to achieve quantitative understandings of system-level E. coli chemotaxis behaviors and their underlying molecular level mechanisms. We will develop mathematical models of protein interaction network and its dynamics based on structural and biochemical details of the chemotaxis signaling pathway. These models will be studied by using analytical analysis and numerical simulation methods. The results from these models will be used to explain experimental data and make testable predictions. The iterative comparison between models and experimental data will be used to improve/refine the models. In this proposal, we will focus on studying two essential aspects of the E. coli chemotaxis pathway: 1) The signaling dynamics and function of the chemorecetor array. We will investigate how the mixed receptor array can distinguish different stimuli (signals) and how the cell makes decision based on the information. We want to study the effect of ATP hydrolysis in sensor kinase signaling and how it modulates the kinase response sensitivity to receptor ligand binding. 2) The switching mechanism for flagellar motor and its dependence on mechanical signals. We want to understand how the flagellar motor can be controlled by changes in its mechanical environment (force, load) in addition to the intracelur chemical signals. In summary, we plan to investigate and understand how an E. coli cell senses different (chemical and physical) signals, how it processes this information, and how it makes decisions in complex environments with multiple, time varying cues.