Cross-species Analysis of Bacterial Gene Networks

项目摘要/摘要 理论基础：基因网络支撑着细菌生理学的各个方面。这些网络减少了抗生素 在抗生素耐药性背景下诱导应激，并驱动微生物-微生物和微生物-宿主相互作用 在人类微生物群的背景下。尽管基因网络在维持生存能力和 在组织应激反应方面，很少有研究系统地比较 细菌种类。化学-基因、基因-基因和基因-启动子相互作用的模式将提供线索 基因的功能，途径和调节，拓宽了我们对遗传背景如何 菌株会改变网络连接。 目的：我们提出了三种肠道遗传和调控网络的跨物种比较。 与人类健康相关的物种：大肠杆菌、阴沟肠杆菌和肺炎克雷伯氏菌。 与研究充分的模型E.ColiK-12的比较将推动阴沟肠杆菌和K. 肺炎，以及为未来的跨物种比较提供了试验台。为了便于这些分析， 我们已经开发了基于CRISPR的工具，这些工具可以很容易地跨物种移植，并可以用于 在基因组水平上研究基因的功能和调控。我们试图揭示基本的机制 通过识别保守的途径来研究动态平衡和应激反应。我们的基础研究方法可以 针对细菌病原体基因网络中的弱点的通知策略或可应用于 在人类微生物组的背景下检查宿主修改的网络。

PROJECT SUMMARY/ABSTRACT Rationale: Gene networks underpin all aspects of bacterial physiology. These networks mitigate antibiotic induced stress in the context of antibiotic resistance, and drive microbe-microbe and microbe-host interactions in the context of the human microbiome. Despite the central role of gene networks in maintaining viability and organizing stress responses, there have been few studies that systematically compare gene networks across bacterial species. Patterns in chemical-gene, gene-gene, and gene-promoter interactions will provide clues to gene functions, pathways, and regulons, broadening our understanding of how the genetic backgrounds of strains alter network connectivity. Objective: Here we propose a cross-species comparison of genetic and regulatory networks in three enteric species relevant to human health: Escherichia coli, Enterobacter cloacae, and Klebsiella pneumoniae. Comparisons to the well-studied model, E. coli K-12, will drive gene function discovery in E. cloacae and K. pneumoniae, as well as provide a test bed for future cross species comparisons. To facilitate these analyses, we have developed CRISPR-based tools that are easily portable across species and can be used to investigate gene function and regulation at the genome scale. We seek to uncover fundamental mechanisms of homeostasis and stress responses by identifying conserved pathways. Our basic research approach could inform strategies that target weak points in gene networks of bacterial pathogens or could be applied to examine host-modified networks in the context of the human microbiome.