The contribution of phenotypic diversity and temporal variability to population signal transduction

表型多样性和时间变异对群体信号转导的贡献

• 批准号: 9901543
• 负责人: Thierry Emonet
• 金额: $ 34.31万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9901543
• 关键词: Affect; Assimilations; Bacteria; Behavior; Biological Models; Biological Process; Cell Cycle; Cell Cycle Regulation; Cell Signaling Process; Cell division; Cells; Cellular biology; Chemotaxis; Clone Cells; Complex; Data; Dependence; Detection; Escherichia coli; Exhibits; Fluorescence Resonance Energy Transfer; Funding; Gene Expression; Genes; Goals; Growth; Individual; Masks; Measurement; Measures; Memory; Microbiology; Microfluidics; Modeling; Molecular; Noise; Pathway interactions; Performance; Phase; Phenotype; Phosphotransferases; Play; Population; Population Heterogeneity; Population Process; Positioning Attribute; Process; Property; Proteins; Public Health; Race; Role; Sensory; Shapes; Signal Pathway; Signal Transduction; Source; Stimulus; Swimming; System; Techniques; Technology; Time; Variant; cell growth; computer framework; individual response; response; signal processing; statistics; technological innovation; theories

Project Summary: Biological functions are typically performed by groups of cells that predominantly express the same genes yet display a continuum of phenotypes. The long-term goal of this project is to understand how such variations influence functional properties at the population level, which is a fundamental problem in cell biology with critical implications for public health. As a model system, we have been using the bacterial chemotaxis system of Escherichia coli because it involves non-trivial functions, such as signal detection, amplification, memory and adaptation, and it is well-characterized molecularly. During the previous funding cycle, we developed microfluidics and computational technology to measure protein abundance, swimming behavior, and performance of the same individual cells in a race up a gradient of attractant. These data revealed that chemotactic performance depends nonlinearly on swimming phenotype, which in turn depends nonlinearly on protein abundances. These nonlinearities have important consequences: because the average of a nonlinear function is different from the nonlinear function of the average, the population could outcompete the performance of its mean phenotype in some conditions. This result illustrates a basic and ubiquitous mechanism by which phenotypic diversity can modulate function in cell biology, even in the absence of any interactions among cells. In this next funding cycle, we plan to examine the consequence of this mechanism for signal transduction by combining our microfluidics and computational framework with single-cell FRET technology developed by long- term collaborator Dr. Thomas Shimizu. This new combined platform enables high-throughput single-cell measurements of signaling dynamics in microfluidics chambers. Using this approach, we will examine how temporal variations in individual cells, due to spontaneous fluctuations in the pathway (Aim 1) and to cell cycle regulation (Aim 2), affect their ability to process signals. These aims will also quantify the contribution of these processes to the standing variation in an isogenic population. Finally, in Aim 3 we will examine how phenotypic diversity shapes the population’s capability to process signals. Taken together, the proposed aims will go beyond the population-average characterization of this signaling network to reveal how diverse individual cells process signals while growing and fluctuating, and how this diversity shapes the population’s signal transduction capabilities beyond those of its mean phenotype.

项目概要： 生物学功能通常由主要表达相同基因的细胞群执行， 表现出一系列的表型这个项目的长期目标是了解这些变化是如何 在群体水平上影响功能特性，这是细胞生物学中的一个基本问题， 对公共卫生的影响。作为一个模型系统，我们一直在使用的细菌趋化系统， 大肠杆菌，因为它涉及非平凡的功能，如信号检测，放大，记忆和 适应，它是分子特征。 在上一个资助周期中，我们开发了微流体和计算技术来测量蛋白质 丰度，游泳行为，和相同的单个细胞在一个梯度的比赛中的表现。 引诱剂这些数据揭示了趋化性能非线性地依赖于游泳表型， 这又非线性地依赖于蛋白质丰度。这些非线性具有重要的后果： 因为非线性函数的平均值不同于平均值的非线性函数， 在某些条件下，可以胜过其平均表型的表现。这一结果说明了一个基本的， 表型多样性可以调节细胞生物学功能的普遍机制，即使在缺乏 任何细胞间的相互作用。 在下一个资助周期中，我们计划通过以下方式研究这种信号转导机制的后果： 结合我们的微流体和计算框架与单细胞FRET技术开发的长期， 长期合作者清水托马斯博士。这种新的组合平台能够实现高通量单细胞 测量微流体室中的信号动力学。使用这种方法，我们将研究如何 单个细胞中的时间变化，由于途径中的自发波动（Aim 1）和细胞周期 调节（目标2），影响他们处理信号的能力。这些目标还将量化这些方面的贡献。 对同基因群体中现存变异的影响。最后，在目标3中，我们将研究表型 多样性塑造了人口处理信号的能力。总的来说，拟议的目标将超越 这个信号网络的群体平均特征，以揭示不同的个体细胞如何处理 信号，同时增长和波动，以及这种多样性如何塑造人口的信号转导 超越其平均表型的能力。