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

职业：揭示个体微生物和群体异质决策的综合方法

基本信息

批准号：
2045493
负责人：
Megan McClean
金额：
$ 62.99万
依托单位：
University of Wisconsin-Madison
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-02-15 至 2026-01-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2045493&HistoricalAwards=false
关键词：
CAREER Synthetic approaches unravel heterogeneous

项目摘要

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.

遗传物质水平相同的微生物仍然可能表现不同（这称为“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目标的因素。该项目的目的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群体的影响是什么。我们将使用新工具，使我们能够用光控制细胞过程，以确定不同因素的影响。（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，除了这项研究之外，我们还将测量微生物种群在不同压力和药物治疗下的生长和生存情况。该项目将侧重于开发工程和生命科学研究领域的人力资源，从中学阶段开始一直到研究生阶段。该项目将研究研究方法和结果，以开发新课程和导师。开发专门针对中学生的外展和教育材料，包括创新的交互式建模游戏，将提高学生的科学素养并保持学生的 STEM 能力。该项目将利用合成和定量生物学的新方法来理解（1 ）效应子活动的动态性和异质性如何与其他细胞成分相互作用，从而导致细胞间的基因表达变异；（2）个体微生物决策的异质性如何决定种群水平的表型，例如生长和抗逆性。将使用酵母来实现这些目标酿酒酵母并将新的光遗传学工具与基因表达测量、单细胞决策和转录因子活性的光遗传学控制相结合来控制效应子（特别是转录因子，TF）活性，并与计算模型相结合，使我们能够实现这一目标。 (1) 识别传播或抑制同源 TF 活性波动的转录靶标；(2) 表征 TF 活性如何动态转录控制爆发。此外，表征异质决策的方式。确定同基因微生物群体中的群体水平表型，我们将量化生长和应激存活，同时使用 TF 活性的光遗传学控制来调节基因表达的细胞间变异。这项研究的结果将加深对效应子活动如何影响观察到的结果的理解。个体微生物之间基因表达和表型使命的异质性以及这种异质性对群体水平结果的影响。该奖项反映了 NSF 的法定规定，并通过使用基金会的智力价值和更广泛的影响审查进行评估，被认为值得支持标准。