Cell-to-Cell Variability in Chemotactic Signal Integration

趋化信号整合的细胞间变异

• 批准号: 10313078
• 负责人: Jeremy Philippe Moore
• 金额: $ 4.6万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-17 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10313078
• 关键词: Cell; Variability; Chemotactic; Signal; Integration

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.

项目摘要 细胞间基因表达的变异性和生化反应的随机性使得 单个基因型产生许多不同的表型。这种非遗传多样性与 医学意义，因为它导致病原菌的抗生素持久性， 增强毒力行为。因此，理解细胞间变异性在细胞内的作用， 微生物种群的行为具有关键的临床重要性。拟议的工作将 确定细菌种群如何利用细胞间的变异性来处理复杂的 环境信号。具体来说，我们将学习如何适应机制的高度 保守的细菌趋化性网络允许群体调节细胞间的变异性， 当存在背景信号时，对不同刺激的敏感性。然后，我们将学习如何 不同的化学效应物的优先检测在细菌群体中不同，并且是否 种群划分信号劳动以检测和响应刺激混合物。这些问题 将使用我们实验室开发的一种新型微流控装置来回答，该装置可以快速应用- 将刺激物切换到细胞群体。对趋化性刺激的反应将用 完善的FRET报告系统，最近进一步开发用于单- 细胞测量凭借我们广泛的定量专业知识，我们将使用我们的测量， 约束细胞间变异性如何影响信号处理的数学模型， 群体，以及不同的群体如何处理与单细胞不同的信号。