Revealing Stochastic Switches in Bacteria

项目摘要 随机开关是一种广泛的遗传机制，它使单细胞能够切换某些基因 随机开关，不对环境做出反应。这种开关在致病性 细菌，其中它们通常参与产生跨细菌的不同表面蛋白库。 群体，这使得一个子集的细胞，以避免检测由免疫系统。一般来说，随机 开关提供了一种在波动环境中生存的策略，通过维持细胞的亚群， 预先适应的状态，为未来可能不可预测的环境压力做好准备。特别是， 已知这些策略在抗生素持久性中是重要的，抗生素持久性是一种非遗传的、可逆的、生理性的， 在细菌细胞亚群中出现的对抗生素的耐受性增强的状态。 这项资助适用于新的微流体设备，使单细胞观察持久的细胞谱系， 转录组学和生物信息学来研究随机转换的三个主要方面。我们使用显微镜， 合成生物学，以了解为什么细菌聚集，一种行为，提高生存下 抗微生物治疗，是由随机切换，以及如何逆转聚集状态使用小 关键遗传途径的分子抑制剂。我们使用一种新颖的定制微流体装置，使单- 对数十万个细胞进行细胞谱系跟踪，以观察抗生素持续状态， 以前观察到的，并应用转录组学揭示持久性的分子机制。我们使用一个 一种新的群体遗传学方法来模拟细菌重组，可以灵活地应用于推断 大规模基因组和宏基因组测序数据集的重组参数。我们应用此 一种研究随机开关如何在人类肠道中受重组影响的方法 微生物组 拟议的研究将大大推进对随机开关作用的理解， 聚集和重组的细菌适应。通过强调精确的量化， 强大的单细胞微流体和显微镜，这项研究将产生新的途径，以解决抗生素 细菌的持久性，扰乱细菌的聚集状态，并了解人类肠道 环境选择并维持抗生素抗性和表面抗原基因。

PROJECT SUMMARY Stochastic switches are a broad class of genetic mechanisms that enable single cells to switch certain genes on and off randomly, without responding to their environment. Such switches are prevalent in pathogenic bacteria, where they are often involved in generating diverse surface protein repertoires across the bacterial population, which enables a subset of cells to avoid detection by the immune system. In general, stochastic switches provide a strategy for survival in fluctuating environments, by maintaining subpopulations of cells in pre-adapted states that are prepared for future, possibly unpredictable, environmental stresses. In particular, these strategies are known to be important in antibiotic persistence, a non-genetic, reversible, physiological state with enhanced tolerance for antibiotics that occurs in a subpopulation of bacterial cells. This grant applies novel microfluidic devices that enable single cell observations persister cell lineages, with transcriptomics, and bioinformatics to study three major facets of stochastic switching. We use microscopy and synthetic biology to understand why bacterial aggregation, a behavior that enhances survival under antimicrobial treatment, is regulated by stochastic switching, and how to reverse aggregate states using small molecule inhibitors of key genetic pathways. We use a novel custom microfluidics setup that enables single- cell lineage tracking on hundreds of thousands of cells to observe antibiotic persister states that could not previously be observed, and apply transcriptomics to reveal molecular mechanisms of persistence. We use a new population genetic approach to modeling bacterial recombination, which can be flexibly applied to infer recombination parameters from large-scale genomic and metagenomic sequencing datasets. We apply this method to study how stochastic switching is influenced by recombination in the context of the human gut microbiome. The proposed research will substantially advance understanding of the role of stochastic switches, aggregation, and recombination in bacterial adaptation. Through its emphasis on precise quantification using powerful single cell microfluidics and microscopy, the research will yield new avenues to address antibiotic persistence of bacteria, to perturb bacterial aggregated states, and to understand how the human gut environment selects for and maintains antibiotic resistance and surface antigen genes.