System-level properties of the E. coli metabolic network

描述(由申请人提供)：调查者是西北大学医学院学术实践的内科科学家，主要研究兴趣是系统生物学/功能基因组学，并对分子病理学有相应的临床兴趣。该机构通过建立跨学科研究计划--基因组医学中心，展示了对后基因组生物学及其对医学的影响的坚定承诺。申请人的研究兴趣源于这样一种认识，即离散的生物功能以及各种疾病实体大多不能仅仅归因于单个分子的功能。相反，生物系统的强健行为在很大程度上源于其各种建筑组件(即细胞网络)之间的复杂相互作用。在这项申请中，我们建议进行一个高度集成的计划，在该计划中，我们将定量地检查维持细胞正常功能所需的复杂代谢网络的结构。请注意，这项研究代表了申请者与理论物理学家(A.-L.Barabasi)和细菌/遗传学家(B.L.Wanner)之间的独特合作。这项建议的具体目标如下：(1)我们将定量分析模式生物(如大肠杆菌)的复杂代谢和遗传网络的结构和功能活性；(2)我们将研究扰动中心代谢网络中蛋白质水平以帮助建立模型的影响，并测试从这些模型的计算机模拟中演变出来的规则，包括检查它们对靶向突变的耐受性；以及(3)在对大肠杆菌生理组的研究中，我们将试图了解代谢网络中随着环境变化而发生的动态变化。了解活细胞各种代谢网络成分之间相互作用的原理和代谢网络的一般规模性特征，不仅对基础生物学有重要贡献，而且对抗菌药物靶标识别等翻译研究也具有适用性。

DESCRIPTION (provided by applicant): The investigator is a physician-scientist in academic practice at Northwestern University Medical School with a primary research interest in systems biology/functional genomics and a corresponding clinical interest in Molecular Pathology. This institution has demonstrated a strong commitment to post-genomic biology and its implications to medicine by the establishment of the Center for Genomic Medicine, an inter-disciplinary research initiative. The applicant's research interest stems from the recognition that discrete biological functions, and thus various disease entities, mostly cannot be attributed only to the function of individual molecules. Instead, the robust behavior of biological systems arises to a large extent from complex interactions among its various building constituents (i.e., cellular networks). In this application, we propose to conduct a highly integrated program in which we will examine in quantitative terms the structure of complex metabolic networks that are required to maintain the proper function of a cell. Note that this research represents a unique collaboration between the applicant and a theoretical physicist (A.-L. Barabasi), and a bacteria/geneticist (B. L. Wanner). Specific goals for the proposal are the following: (1) We will analyze in quantitative terms the structure and functional activity of complex metabolic and genetic networks of model organisms, such as Escherichia coli, (2) We will examine the effects of perturbing the levels of proteins in central metabolic networks to aid in model building and to test rules that evolve from computer simulations of these models, including examining their tolerance to targeted mutations; and (3) We will attempt to develop an understanding of the dynamic changes that take place in metabolic networks in response to a changing environment, in studies of the Escherichia coli physiome. Understanding the principles of interactions among various metabolic network components of a living cell and the generic large-scale feature of metabolic networks will provide both an important contribution to basic biology, and will also have applicability to translational research, such as antibacterial drug target identification.