Network Analysis of Pathogenicity in Pseudomonas aeruginosa

描述(申请人提供)：高通量技术正在产生大量关于人类病原体细胞功能的数据。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。一个关键的障碍是，测序分析工作确定的目标没有考虑细胞内的相互作用网络；例如，考虑到系统中路径的冗余，抑制一种蛋白质的功能可能没有效果。我们建议重建和验证铜绿假单胞菌的代谢和调控网络，特别关注先前发现的对其毒力至关重要的突变株。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，非常需要一个量化框架，可以用来对高通量数据进行上下文分析，生成表型预测，并提出关于其生理的可测试的假设。具体地说，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)表征先前在签名标记突变筛选中发现的无毒铜绿假单胞菌单基因突变株在最低培养条件下的代谢表型；以及(3)分析囊性纤维化特异性培养基中铜绿假单胞菌和无毒突变株的代谢表型，以开发基于条件必需基因的可能的治疗策略。这一拟议计划的结果将是一个表征良好、验证良好的铜绿假单胞菌模型，该模型可用于系统地确定药物靶标和其致病性的关键特征，以及描绘STM鉴定的突变体的关键代谢表型(例如，生长速度、副产品分泌)，这些突变体可能用于开发治疗策略。拟议的计划将导致迄今为止对具有重大疾病负担的病原体进行最全面的重建。 公共卫生相关性：拟议的计划将导致迄今为止最全面的人类病原体重建。铜绿假单胞菌除了在医院获得性感染中造成重大疾病负担外，在烧伤患者、囊性纤维化患者、接受化疗方案的癌症患者和其他免疫功能低下的患者中也是一个重大问题。此外，耐药性已经是铜绿假单胞菌感染的一个重要问题，而且在未来肯定会是一个更大的挑战。这一拟议计划的结果将是一个具有良好特征、经过良好验证的铜绿假单胞菌模型，可用于系统地确定药物靶标和其致病性的关键特征。

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. PUBLIC HEALTH RELEVANCE: The proposed program will lead to the most comprehensive reconstruction to date of a human pathogen. Aside from its significant disease burden in hospital-acquired infections, Pseudomonas aeruginosa poses a significant problem in burn patients, individuals with cystic fibrosis, cancer patients on chemotherapy regimens, and other immuno-compromised individuals. Furthermore, drug resistance is already an important problem in P. aeruginosa infections and will certainly be an even greater challenge in the future. 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.