Network Analysis of Pathogenicity in Pseudomonas aeruginosa

描述（由申请人提供）：高通量技术正在生成关于人类病原体细胞功能的大量数据。然而，尽管对数百种病原体进行了基因组测序，但基因组学方法在确定可行的药物靶点方面取得的成功有限。一个关键障碍是，测序分析工作确定的目标没有考虑到细胞内的相互作用网络;例如，考虑到系统中途径的冗余，抑制一种蛋白质的功能可能没有任何影响。我们建议重建和验证铜绿假单胞菌的代谢和调控网络，特别注意以前确定的突变体已知是其毒力的关键。为了在这种人类病原体的细胞内网络的背景下开发治疗策略，存在对可用于情境化高通量数据、生成表型预测并提出关于其生理学的可检验假设的定量框架的显著需要。具体而言，我们提出的目标是：（1）重建铜绿假单胞菌的代谢和调控网络，以解释1500个基因的功能，这将导致迄今为止最大的病原体网络重建;（2）表征在基本培养基条件下的无毒铜绿假单胞菌单基因突变体的代谢表型，先前在签名标记的诱变筛选中鉴定;（3）分析铜绿假单胞菌和无毒突变株在囊性纤维化特异性培养基中的代谢表型，以开发基于条件必需基因的可能的治疗策略。该拟议计划的结果将是一个经过充分表征、验证的铜绿假单胞菌模型，可用于系统地识别药物靶点及其致病性的关键特征，以及描述关键代谢表型（例如，生长速率、副产物分泌物），其可以潜在地用于开发治疗策略。拟议的计划将导致迄今为止最全面的重建病原体与重大疾病负担。

DESCRIPTION (provided by applicant): High-throughput technologies are generating a tremendous amount of data about cellular functions of human pathogens. However, despite the genome sequencing of hundreds of pathogens, the genomics approach has had limited success at identifying viable drug targets. One key hurdle has been that targets identified by sequencing analysis efforts do not take into account the network of interactions inside the cell; for instance, inhibiting the function of one protein may have no effect given the redundancy of pathways in the system. We propose to reconstruct and validate the metabolic and regulatory networks of Pseudomonas aeruginosa, with particular attention to previously identified mutants known to be critical for its virulence. In order to develop therapeutic strategies in the context of the intracellular networks in this human pathogen, there exists a significant need for a quantitative framework that can be used to contextualize high-throughput data, generate phenotypic predictions, and propose testable hypotheses regarding its physiology. Specifically, our proposed aims are to: (1) Reconstruct the metabolic and regulatory networks of P. aeruginosa to account for the function of 1500 genes, which will result in the largest network reconstruction of a pathogen to date; (2) Characterize the metabolic phenotypes under minimal media conditions of avirulent P. aeruginosa single-gene mutants identified previously in a signature-tagged mutagenesis screen; and (3) Analyze metabolic phenotypes of P. aeruginosa and avirulent mutant strains in cystic fibrosis-specific medium to develop possible therapeutic strategies based on conditionally essential genes. The outcome of this proposed program will be a well-characterized, well-validated model of P. aeruginosa that can be used for systematically identifying drug targets and key features of its pathogenicity, as well as a delineation of the key metabolic phenotypes (e.g., growth rate, byproduct secretions) of the STM-identified mutants that can be used potentially for the development of therapeutic strategies. The proposed program will lead to the most comprehensive reconstruction to date of a pathogen with a significant disease burden.