None-genetic metabolic heterogeneity and its influence on drug tolerance

项目总结 细胞的异质性在生命的各个领域无处不在。基因相同的细胞可以 表现出不同的代谢活动，即使生长在相同的环境中也是如此。在……里面 细菌、代谢异质性会影响菌群的生长速度并影响抗生素 宽容。在高等生物体中，代谢活性在功能上与肿瘤活性和药物有关。 宽容。而细胞在信使核糖核酸和蛋白质丰度上的异质性广泛存在 经过研究，关于代谢异质性的许多问题仍然存在。例如，什么 决定代谢波动的大小和频率？新陈代谢的异质性是如何 受监管？我们能否控制代谢异质性，从而消除耐药细胞？ 对这一重要话题缺乏根本性的理解，严重限制了 开发对多种疾病的有效治疗方法，在这些疾病中，少数一过性 耐受细胞通常会导致疾病复发。在过去的几年里，张实验室已经 开发了几种研究代谢物异质性的方法，包括代谢物生物传感器- 通过细胞分选辅助单细胞成像和代谢物定量。我们的工作发现了大型的， 脂肪酸生物合成中的非遗传异质性，以及我们利用代谢异质性 用于生物技术应用(即化学品生产过剩)。在这个米拉提案中，我们的目标是 通过使用我们的方法系统地了解细菌代谢的异质性 现有的和新的单细胞代谢分析方法。利用大肠杆菌作为发酵剂的研究 模型，我们将构建一个可调节的代谢系统，产生一种独特的荧光 控制流量和代谢物浓度的代谢物。微流体辅助延时测量 荧光显微镜将被用来同时量化这一物质的浓度 代谢物及其生物合成酶、细胞生长速度和单个细胞的年龄。数据 将使用分析和建模相结合的方法来确定原点、动力学和传播 代谢异质性。此外，以天然脂肪酸分解代谢途径为模型， 我们将研究转录和变构调节如何影响代谢异质性。在……里面 此外，我们还将探讨代谢异质性对药物耐受性的影响，并寻求 减少代谢的异质性和多变性。这个项目将揭示新的原理， 管理代谢异质性，并提供一个量化框架来解释各种单一的 细胞现象。理解代谢异质性的调节及其对 药物耐受性将成为消除对甲氧西林不敏感的异种变异的策略 药物，从而为复发性疾病提供了新的治疗方法。

PROJECT SUMMARY Cellular heterogeneity is ubiquitous across all domains of life. Genetically identical cells can display heterogeneous metabolic activities, even when grown in identical environments. In bacteria, metabolic heterogeneity can shape the ensemble growth rate and affect antibiotic tolerance. In higher organisms, metabolic activity is functionally related to tumor activity and drug tolerance. While cellular heterogeneities in mRNA and protein abundance have been extensively studied, many questions remain regarding metabolic heterogeneity. For instance, what determines the size and frequency of metabolic fluctuation? How is metabolic heterogeneity regulated? Can we control metabolic heterogeneity and therefore eliminate drug-tolerant cells? The lack of fundamental understanding about this important topic has severely limited the development of effective treatments for multiple diseases in which a small number of transiently tolerant cells often cause disease recurrence. Over the past few years, the Zhang lab has developed several methods to study metabolite heterogeneity, including metabolite-biosensor- assisted single-cell imaging and metabolite quantification by cell sorting. Our work identified large, non-genetic heterogeneity in fatty acid biosynthesis, and we exploited metabolic heterogeneity for biotechnology applications (i.e. overproduction of chemicals). In this MIRA proposal, we aim to obtain a systematic understanding of bacteria metabolic heterogeneity by using our existing and novel methods for single-cell metabolic analysis. Using Escherichia coli as a model, we will construct a tunable metabolic system that produces a unique fluorescent metabolite with controlled flux and metabolite concentration. Microfluidics-assisted time-lapse fluorescent microscopy will be used to simultaneously quantify the concentrations of this metabolite and its biosynthetic enzyme, the cell growth rate, and the age of single cells. Data analysis combined with modeling will be used to determine the origin, dynamics, and propagation of metabolic heterogeneity. Furthermore, using the native fatty acid catabolic pathway as a model, we will study how transcriptional and allosteric regulations affect metabolic heterogeneity. In addition, we will explore the influence of metabolic heterogeneity on drug tolerance and seek to reduce metabolic heterogeneity and multimodality. This project will reveal novel principles that govern metabolic heterogeneity and provide a quantitative framework to explain various single- cell phenomena. Understanding the regulation of metabolic heterogeneity and its influence on drug tolerance will inform strategies to eliminate heterogeneous variants that are insensitive to drugs, thus providing new treatments for recurrent diseases.