Quantitative Studies of Bacterial Growth Physiology

 描述(申请人提供)：了解细胞应激反应是系统生物学的重大挑战之一。以前对细菌应激反应的研究主要集中在特定的途径或系统范围的遗传反应调查上。在这项提议中，我们描述了对大肠杆菌渗透反应的定量生理研究，解决了渗透胁迫如何影响细菌生长，细菌反应如何缓解施加的压力，以及压力反应给生长带来了什么问题。这些结果将被用来构建渗透反应的成本效益分析，在一个定量的预测性理论的背景下，准确地描述细胞资源的协调，以应对渗透胁迫和维持生物量增长的相互冲突的需求。这项研究的实验部分将涉及现代组学方法和经典生化分析的结合。蛋白质组学和RIBO-SEQ方法将被用来获得细胞蛋白质组资源分配的定量、蛋白质组范围的图像，代谢组学方法将被用来表征营养的使用，对渗透反应和生物量生长的影响。传统的生化方法将被用来监测细胞质和细胞膜的拥挤情况，并检测在非常高的内部浓度下可能发生的渗透压渗漏。这些研究将在不同的营养和中等渗透压下进行，并针对不同的遗传背景，旨在探索渗透反应的各个方面。在理论和实验的迭代对话中，生成的数据将使用HWA实验室首创的粗粒化方法进行分析，以推导出蛋白质组和代谢资源分配的定量模型。

 DESCRIPTION (provided by applicant): Understanding cellular stress response is one of the grand challenges of systems biology. Previous studies of bacterial stress response have focused mostly on either specific pathways or system-wide survey of genetic responses. In this proposal, we describe a quantitative physiological study of E. coli's osmotic response, addressing how osmotic stress affects bacterial growth, how bacterial response alleviates the imposed stress, and what problems the stress response imposes on growth. The results will be used to construct a cost-benefit analysis of the osmotic response, in the context of a quantitative, predictive theory that accurately describes the coordination of cellular resources towards the conflicting demands of combating osmotic stress and maintaining biomass growth. The experimental component of this research will involve a combination of modern 'omic methodologies and classical biochemical analysis. Proteomics and ribo-seq methods will be used to obtain quantitative, proteome-wide picture of the cell's allocation of proteomic resources, and metabolomics methods will be used to characterize the use of nutrients, towards osmotic response vs biomass growth. Traditional biochemical methods will be used to monitor the crowding of the cytoplasm and the membrane, and detect possible leakage of osmolytes maintained at very high internal concentrations. These studies will be done at a variety of nutrient and medium osmolarities, and for different genetic backgrounds designed to probe various aspects of the osmotic response. The data generated will be analyzed using a coarse-graining approach pioneered by the Hwa lab to derive a quantitative model of proteomic and metabolic resource allocation, in an iterative dialogue between theory and experiment.