Revealing Stochastic Switches in Bacteria

项目总结 随机开关是一类广泛的遗传机制，它使单个细胞能够切换某些基因 随机地断断续续，不对环境做出反应。这种开关在致病性疾病中普遍存在 细菌，它们经常参与在细菌中产生不同的表面蛋白谱系 种群，这使得一部分细胞可以避免被免疫系统检测。一般而言，随机性 交换机为在多变的环境中生存提供了一种策略，通过在 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， 众所周知，这些策略在抗生素持久性方面非常重要，这是一种非遗传的、可逆的、生理学的 对细菌细胞亚群中出现的抗生素耐受性增强的状态。 这项资助适用于新型微流控设备，这种设备能够通过姊妹细胞谱系观察单细胞， 转录学和生物信息学来研究随机切换的三个主要方面。我们使用显微镜和 合成生物学来理解为什么细菌聚集，一种在 抗菌治疗，是通过随机切换来调节的，以及如何使用小的 关键遗传途径的分子抑制物。我们使用一种新的定制微流控装置，使单一- 对数十万个细胞进行细胞谱系跟踪，以观察不能维持抗生素的状态 以前被观察到，并应用转录组学来揭示持久性的分子机制。我们使用一种 一种新的模拟细菌重组的群体遗传学方法，可以灵活地应用于推断 来自大规模基因组和元基因组测序数据集的重组参数。我们适用这一点 研究人类肠道环境中重组如何影响随机切换的方法 微生物组。 拟议的研究将极大地促进对随机开关作用的理解， 细菌适应中的聚集和重组。通过强调精确量化，使用 强大的单细胞微流体和显微镜，这项研究将为解决抗生素问题提供新的途径 细菌的持久性，扰乱细菌的聚集状态，并了解人类肠道如何 环境选择并维持抗生素耐药性和表面抗原基因。

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.