Cell-to-Cell Variability in Chemotactic Signal Integration

项目摘要 基因表达的细胞间变异性和生化反应中的随机性允许 单一的基因可以产生多种不同的表型。这种非遗传多样性与 医学意义，因为它会导致病原菌中的抗生素持久性，并可能 增强毒力行为。因此，了解细胞间的可变性在 微生物种群的行为具有重要的临床意义。拟议的工作将 确定细菌群体如何利用细胞间的可变性来处理复杂的 环境信号。具体地说，我们将学习如何高度适应 保守的细菌趋化网络允许种群调节细胞间的可变性 当背景信号存在时，对不同刺激的敏感性。然后，我们将学习如何 不同的化学效应因子在细菌种群中的优先检测是不同的，以及 种群划分发出劳动信号，以检测和回应刺激混合。这些问题 将使用我们实验室开发的一种新型微流控设备来回答，该设备可以快速应用于- 将刺激信号转换为细胞群体。对趋化刺激的反应将通过 完善的FRET报告器系统，最近被进一步开发用于单 细胞测量。凭借我们广泛的量化专业知识，我们将利用我们的测量结果 通过以下方式约束细胞间的可变性如何影响信号处理的数学模型 以及不同的种群如何处理与单一细胞不同的信号。

Project Summary Cell-to-cell variability in gene expression and stochasticity in biochemical reactions allow a single genotype to generate many different phenotypes. This non-genetic diversity has relevant medical implications since it leads to antibiotic persistence in pathogenic bacteria and may enhance virulence behaviors. Thus, understanding the role of cell-to-cell variability in the behavior of microbial populations is of critical clinical importance. The proposed work will determine how bacterial populations utilize cell-to-cell variability to process complex environmental signals. Specifically, we will learn how the adaptation machinery of the highly conserved bacterial chemotaxis network allows populations to modulate cell-to-cell variability in sensitivity to different stimuli when background signals are present. Then, we will learn how preferential detection of different chemoeffectors varies in bacterial populations, and whether populations divide signaling labor to detect and respond to stimulus mixtures. These questions will be answered using a novel microfluidic device developed in our lab which can apply fast- switching stimuli to cell populations. Responses to chemotactic stimuli will be determined with a well-established FRET reporter system which was recently further developed for use in single- cell measurements. With our extensive quantitative expertise, we will use our measurements to constrain a mathematical model of how cell-to-cell variability affects signal processing by populations, and how diverse populations process signals differently from single cells.