Comprehensive genetic characterization of antibiotic resistance

我们建议开发和应用一套全面的实验和 揭示中国人群抗生素耐药遗传基础的计算方法 大肠埃希菌。我们方法的核心是基于微阵列的基因 足迹技术，提供全球范围的定量评估 在抗生素的作用下，基因组中的每一个基因都有助于生存 曝光。已识别的基因将被置于遗传和 通过应用一种新的全基因组上位性来调节网络 分析框架。我们的目标是探索对亚致命疾病的温和抵抗力 抗生素暴露和严重耐受性，如在 ‘坚持不懈’。初步研究提供了强有力的原则性证据 我们提出的框架。我们的方法在大肠杆菌趋化性研究中的应用 在几周的时间范围内识别95%的已知位置，揭示组织 将这些基因座分解为功能子模块，并识别 调节运动性的上下文相关表达。此外，在一个 被广泛研究了三十多年的表型，我们发现了三种 另外十几个新的基因座通过不同的机制做出贡献，包括 RCS信号通路和环-双-GMP第二信使系统。这个 我们的方法在轻微和致命的抗生素暴露中的应用已经 揭示了十几个基因座戏剧性的遗传扰动 提高对抗生素的耐受性。拟议的工作有望显著地 扩大涉及的基因数量，并通过上位性的辅助使用， 共同表达和共同遗传分析使我们能够将这些基因放置在 遗传和监管网络的背景。我们预计我们的发现将 从根本上促进对抗生素耐药性的理解，并提供 生物医学社区具有良好的特征路径，作为 为开发新药奠定了基础。

We propose to develop and apply a comprehensive set of experimental and computational methods for revealing the genetic basis of antibiotic tolerance in Escherichia coli. At the core of our approach is a microarray-based genetic footprinting technology that provides a global quantitative assessment of how each and every gene in the genome contributes to survival under antibiotic exposure. The identified genes will be placed within the context of genetic and regulatory networks through the application of a novel genome-wide epistasis analysis framework. We aim to explore both mild resistance to sub-lethal antibiotic exposure and severe tolerance as expressed in the context of `persistence'. Preliminary studies provide strong proof-of-principle evidence for the framework we propose. Application of our approach to E. coli chemotaxis identifies 95% of known loci on the time-scale of weeks, reveals the organization of these loci into functional sub-modules, and identifies signaling pathways that regulate the context-dependent expression of motility. Furthermore, in a phenotype that has been extensively explored for over thirty year, we find three dozen additional novel loci that contribute through diverse mechanisms including the Rcs signaling pathway and cyclic-di-GMP second messenger system. The application of our approach to mild and lethal antibiotic exposure has already revealed more than a dozen loci whose genetic perturbations dramatically increase antibiotic tolerance. The proposed work promises to significantly expand the number of genes involved, and through the adjunct use of epistasis, co-expression, and co-inheritance analysis, allow us to place these genes within the context of genetic and regulatory networks. We expect our findings to fundamentally advance the understanding of antibiotic resistance and to provide the biomedical community with well-characterized pathways that serve as the basis for the development of new drugs.