Quantitative Modeling of Signal Transduction in Bacterial Chemotaxis

这项研究项目的长期目标是实现对 大肠杆菌趋化作用中的信号转导途径。我们想要整合关于大肠杆菌的知识 不同(长度和时间)尺度上趋化信号通路的数学描述(模型) 该系统可以用来解释和定量预测大肠杆菌对任何 给定的时间和空间信号(刺激)。这些模型将基于已知的分子构建 信号通路的细节和与实验数据相当的适当分辨率。这些 将使用统计物理方法、蒙特卡罗模拟和动力系统来研究模型 分析。这些模型的结果将用于解释现有数据，做出可测试的预测，并 与实验数据的比较将反馈到改进/改进模型。在这项提案中，我们将 关于大肠杆菌趋化途径的两个基本方面：1)(快速)激酶中的信号放大 回应。我们有兴趣找出观察到的信号放大的结构基础，例如，如何 每个合作功能复合体都含有许多受体。我们想要了解分子。 在大肠杆菌趋化性中观察到的高敏感性的大动态范围的机制。我们想要 了解电池如何实现这些卓越的特性(高增益、高灵敏度 背景)具有可变(噪声)内部组件。2)(较慢)适应过程的动力学。 想要定量地了解适应动力学，例如，系统适应的速度有多快，以及 适应时间取决于外部刺激强度。我们想要了解适应动力学 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 模拟和预测细胞在其自然环境中运动时的信号通路动态。：？； 在对一个完整的感觉信号进行定量、系统级建模时发展起来的概念和工具 转导通路将有助于理解高等生物的信号通路和感觉系统。 生物体，包括人类。对细菌趋化途径的分子水平的理解是 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. ;