单克隆细胞的表型异质化是指基因型相同的细胞在同一环境下出现表型差异的现象。这是一种普遍存在的生物学现象，在细胞之间实现社会分工以应对各种环境压力及其变化。目前，人们还不清楚表型异质化过程中，单个细胞能否同时呈现多种表型，即表型之间是否相互制约。本研究根据前期实验结果提出：每个细胞的各项生命活动存在能耗上的总量控制，是制约表型发展的主要因素，而且各种表型的能量分配受到生长速度的调控。本课题以大肠杆菌为模型，首先通过定量生理学和数学模型，理论推导出细胞能量的流入、消耗及分配的定量关系，尤其是与生长速度之间的函数关系；然后通过微流控细胞芯片、流式细胞等检测技术，定量测量单细胞的各项生命活动参数，验证上述理论；同时测定与能量和生长调控有关的关键物质浓度以及各种表型细胞的转录组，找到能量分配的关键分子机制。本研究将丰富生物适应环境机制的理论，并在应用领域为微生物防控提供理论指导和药物设计靶点。

Phenotypic heterogeneity or plasticity of clonal cells - phenotype variation among isogenic cells-is a universal phenomenon among various life forms. It is an important population-centric strategy critical for cells to adapt harsh and changing environments. Current understanding is based on characterization of different phenotypes of a clonal population so that single-cell level study is of importance in the identification of genes and biochemicals involving in promoting phenotypic heterogeneity. Based on our previous results, we propose that an energy-governing stringent control exists within single cells and its fast drainage and controlled release of the active energy currency are the early process of phenotypic heterogeneity. Moreover, such control exhibits as growth rate variation that is measurable at both population and single cell levels. Based on quantitative physiology, we will first define all related pathways and develop mathematical models to simulate the process of total energy consumption and allocation for major cellular activities, as well as their quantitative correlations to growth rate. We will define various phenotypes using flow-cytometry, Raman spectrum-based cell sorting instruments, and cell-on-chip devices. We will also examine the concentration of various critical biochemical substances related to energy and growth control, as well as transcriptomes of the phenotypes and try to plot out mechanisms of energy control and allocation. Our work not only will greatly advance our understanding of bacterial adaption to the environment, but also will provide guidance practical for microbial control and potential targets for drug design.