Quantitative Modeling of Signal Transduction in Bacterial Chemotaxis

本研究项目的长期目标是实现定量的，系统的水平理解， E.大肠杆菌趋化性。我们希望将E.杆菌 不同（长度和时间）尺度上的趋化性信号通路转化为数学描述（模型） 该系统可以用来定量解释和预测E.大肠杆菌对任何 给定时间和空间信号（刺激）。模型将基于已知的分子 信号通路的细节，并在适当的分辨率与实验数据相当。这些 模型将使用统计物理方法，蒙特卡罗模拟和动力系统进行研究 分析.这些模型的结果将用于解释现有数据，做出可检验的预测， 与实验数据的比较将反馈以改进/细化模型。在本提案中，我们将 重点讨论了E.大肠杆菌趋化途径：1）（快）激酶中的信号放大 反应我们感兴趣的是找出观察到的信号放大的结构基础，例如，如何 每个协同功能复合物含有许多受体。我们想了解分子。 机制的宽动态范围的高灵敏度观察E。大肠杆菌趋化性。我们想 了解细胞如何实现这些优异的性能（高增益，高灵敏度在广泛的 具有可变（噪声）内部分量的背景）。2)（较慢的）适应过程的动力学。我们 想要定量地了解适应动力学，例如，系统的适应速度以及 适应时间取决于外部刺激强度。我们想了解适应动力学， 时变刺激，例如具有不同斜坡速率的指数斜坡。最终，我们希望能够 模拟和预测细胞在自然环境中移动时的信号通路动力学。：¿; 在完整感觉信号的定量、系统级建模中开发的概念和工具 转导通路将有助于理解信号通路和感觉系统在高等 生物，包括人类。对细菌趋化性途径的分子水平理解是 重要的是研究细菌病原体在人类健康中的作用。;

Thelong 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 fociis 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 fucntional 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 sensitivty over a wide range of backgrounds) with variable (noisy) internal components. 2) Kinetics of the (slower) adaptationprocess.^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. ;