CAREER: Synthetic approaches to unravel heterogeneous decision-making in individual microbes and populations

在遗传物质水平上相同的微生物仍然可以表现不同（这被称为“表型异质性”），理解和控制微生物行为的基本挑战之一是确定控制这种异质性的因素。该项目的目标是了解哪些特定因素控制表型异质性，以及这种异质性对微生物种群的影响。我们将使用新的工具，使我们能够用光控制细胞过程，以确定不同因素（特别是转录因子）对模型微生物：酵母表型异质性的影响。为了确定表型异质性对微生物群落结果的影响，我们将测量微生物种群在不同压力和药物治疗下的生长和存活情况。除了这项研究之外，该项目还将从中学阶段开始，一直到研究生阶段，重点发展工程和生命科学研究领域的人力资源。该项目将整合研究方法和研究成果，以开发新的课程和指导学员。开发专门针对中学生的外展和教育材料，包括创新的互动建模游戏，将提高学生的科学素养，并使他们继续学习STEM。该项目将利用合成生物学和定量生物学的新方法来理解(1)效应活性的动力学和异质性如何与额外的细胞成分相互作用，从而促进基因表达的细胞间变异性；(2)个体微生物决策的异质性如何决定种群水平的表型，如生长和抗逆性。该项目将利用酵母酿酒酵母来实现这些目标，并结合新的光遗传学工具来控制效应物（特别是转录因子，TF）的活性，测量基因表达、单细胞决定和群体水平的结果。光遗传学控制转录因子活性结合计算模型将使我们能够(1)确定传播或抑制其同源TF活性波动的转录靶标；(2)表征TF活性动态如何控制转录爆发。此外，为了描述异质决策如何决定等基因微生物群体的群体水平表型，我们将量化生长和应激生存，同时利用光遗传学控制TF活性来调节基因表达的细胞间变异性。这项研究的结果将增加对效应物活性如何促进个体微生物之间观察到的基因表达和表型异质性的理解，以及这种异质性对群体水平结果的影响。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Microbes that are identical at the level of their genetic material can still behave differently (this is referred to as ‘phenotypic heterogeneity’) and one of the fundamental challenges in understanding and controlling the behavior of microbes is identifying the factors that control this heterogeneity. The goals of this project are to understand which specific factors control phenotypic heterogeneity and what the consequences of this heterogeneity are for populations of microbes. We will use new tools that allow us to control cellular processes with light to determine the effect of different factors (specifically transcription factors) on phenotypic heterogeneity in a model microbe: yeast. To determine the consequences of phenotypic heterogeneity on outcomes for microbial communities we will measure how populations of microbes grow and survive under different stress and drug treatments. In addition to this research, the project will focus on developing human resources at the interface of engineering and life sciences research starting at the middle-school level and reaching through graduate levels. This project will integrate research methods and findings from the research to develop new curricula and mentor trainees. Development of outreach and educational materials aimed specifically at middle-school students, including an innovative interactive modeling game, will enhance science literacy and maintain students in the STEM pipeline.This project will utilize new approaches from synthetic and quantitative biology to understand (1) how the dynamics and heterogeneity of effector activity interact with additional cellular components to contribute to cell-to-cell variability in gene expression and (2) how heterogeneity in individual microbial decisions determines population-level phenotypes such as growth and stress resistance. The project will pursue these objectives using the yeast Saccharomyces cerevisiae and combine new optogenetic tools to control effector (specifically transcription factor, TF) activity with measurement of gene expression, single-cell decisions, and population-level outcomes. Optogenetic control of transcription factor activity in combination with a computational model will allow us to (1) identify transcriptional targets that propagate or suppress fluctuations in their cognate TFs activity and (2) characterize how TF activity dynamics control transcriptional bursting. Furthermore, to characterize how heterogeneous decision-making determines population-level phenotypes in isogenic microbial populations we will quantify growth and stress survival while using optogenetic control of TF activity to modulate cell-to-cell variability in gene expression. The results of this research will increase understanding of how effector activity contributes to observed heterogeneity in gene expression and phenotype between individual microbes and the effect of this heterogeneity on population-level outcomes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.