Evolution of Stress Response Gene Regulatory Network in a Commensal and Opportunistic Yeast Pathogen

共生和机会性酵母病原体中应激反应基因调控网络的进化

基本信息

  • 批准号:
    10459436
  • 负责人:
  • 金额:
    $ 37.71万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-08-01 至 2025-07-31
  • 项目状态:
    未结题

项目摘要

Gene regulatory evolution is a major driver for phenotypic divergence. While this has been well-studied in development, its importance in non-developmental processes is far less understood. The overall vision of the lab is to fully characterize the evolutionary rewiring of gene regulatory networks (GRNs) for major stress responses in opportunistic yeast pathogens, and elucidate the contribution of such changes to the survival and virulence in the host. The lab previously discovered a significant difference in how a commensal and opportunistic yeast pathogen, Candida glabrata, regulates its Phosphate Starvation (PHO) response compared with its non-commensal relative, Saccharomyces cerevisiae: the commensal has dramatically expanded its PHO response targets both in number and in function, which was attributed to derived changes in its master transcription factor (TF) by being less dependent on the co-TF. The goal of the lab in the next five years is to determine the genetic and mechanistic bases of this novel mode of TF evolution, i.e. acquiring new targets by reducing co-TF dependence, and the effect of such evolution on stress resistance to phosphate starvation as well as combinatorial stresses in the host. Understanding how this model stress response evolved by itself and in its interaction with other stress responses will begin to elucidate the principles for stress response evolution in commensal yeasts in general. To reach this goal, three Directions will be pursued: 1) Elucidate the mechanisms of a novel mode of TF evolution and its impact on the downstream response, using biophysical and fitness assays; 2) Dissect the crosstalk between stress responses and how it evolved in commensal yeasts, by determining the interaction of PHO response with oxidative stress and general stress responses in C. glabrata and S. cerevisiae; 3) Determine how the PHO network evolved in other commensal yeasts and related non- commensals, using transcriptome profiling coupled with genome-wide Chromatin-IP. Research proposed in this application is innovative because the evolutionary approach will identify key changes in the wiring of the stress response GRNs underlying host adaptation. The proposed research is significant because it will both shed light on the general principles for GRN evolution, and will provide a conceptual framework for developing novel antifungal strategies targeting stress responses.
基因调控进化是表型分化的主要驱动力。虽然这一点已经得到了很好的研究, 虽然它在发展过程中起着重要作用,但人们对它在非发展过程中的重要性了解甚少。整体视觉 该实验室的目的是充分表征基因调控网络(GRNs)的进化重组, 主要的压力反应在机会酵母病原体,并阐明这种贡献 改变宿主的存活率和毒力。实验室之前发现了一个显著的差异, 光滑假丝酵母是一种机会致病性酵母菌, 饥饿(PHO)反应与其非酿酒亲戚,酿酒酵母: 在数量和功能方面,联合国粮农组织大大扩大了其PHO应对目标, 是由于其主转录因子(TF)的衍生变化, 合作TF。该实验室在未来五年的目标是确定这种现象的遗传和机制基础。 TF演化的新模式,即通过降低co-TF依赖性来获得新靶点,以及 这种进化对宿主对磷饥饿的胁迫抗性以及组合胁迫的抗性。 了解这种模型压力反应本身以及与其他压力的相互作用是如何演变的 反应将开始阐明的原则,应激反应的演变,在酿酒酵母, 将军为了达到这一目标,我们将沿着三个方向进行:1)阐明一种新模式的机制 TF进化及其对下游反应的影响,使用生物物理和健身测定; 2) 通过确定压力反应之间的串扰以及它如何在酵母中进化, 探讨了PHO反应与C. glabrata和S. 3)确定PHO网络如何在其他酿酒酵母和相关的非酿酒酵母中进化。 使用转录组分析结合全基因组染色质-IP。研究提出 在这个应用中是创新的,因为进化的方法将识别布线中的关键变化 宿主适应性的应激反应GRNs。这项研究意义重大,因为它 将阐明GRN发展的一般原则,并将提供一个概念框架 用于开发针对应激反应的新型抗真菌策略。

项目成果

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Bin Z He其他文献

Bin Z He的其他文献

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{{ truncateString('Bin Z He', 18)}}的其他基金

Evolution of Stress Response Gene Regulatory Network in a Commensal and Opportunistic Yeast Pathogen
共生和机会性酵母病原体中应激反应基因调控网络的进化
  • 批准号:
    10227186
  • 财政年份:
    2020
  • 资助金额:
    $ 37.71万
  • 项目类别:
Evolution of Stress Response Gene Regulatory Network in a Commensal and Opportunistic Yeast Pathogen
共生和机会性酵母病原体中应激反应基因调控网络的进化
  • 批准号:
    10673886
  • 财政年份:
    2020
  • 资助金额:
    $ 37.71万
  • 项目类别:
Evolution of Stress Response Gene Regulatory Network in a Commensal and Opportunistic Yeast Pathogen
共生和机会性酵母病原体中应激反应基因调控网络的进化
  • 批准号:
    10026476
  • 财政年份:
    2020
  • 资助金额:
    $ 37.71万
  • 项目类别:

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