SGER: Metabolic Responses to Xenobiotic Chemical Stressors in Microbial Systems

SGER：微生物系统中对异生化学应激源的代谢反应

• 批准号: 0302432
• 负责人: Catherine Peters
• 金额: $ 10万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0302432&HistoricalAwards=false
• 关键词: SGER; Metabolic; Responses; Xenobiotic; Chemical

0302432 Peters There are numerous examples of engineered and natural systems in which the functioning of the system relies on a stable biological community of microorganisms. An excellent example is the activated sludge in an engineered biological treatment system. Perturbation of such systems by xenobiotic chemicals may lead to biological stress and subsequent shifts in the structure and function of the microbial community. Changes manifested at the population level may include diversion of resources away from growth processes, and physiological or evolutionary adaptation of the species. Changes at the community level may include shifts in species diversity, shifts in catabolic function, and alteration of the overall stress tolerance of the community. The key to understanding the link between cellular-level responses to chemical stressors and population- and community-level responses lies in the metabolic responses of individual species. This project seeks to (i) establish methodologies to measure metabolic responses to chemical stressors, and (ii) test a critical hypothesis regarding growth kinetic responses to chemical stressors. Recent work has shown that oxidative chemical stressors evoke the glutathione-gated potassium efflux GGKE) stress response in Gram negative bacteria. This mechanism is expected to impose energy requirements beyond those normally required for cell maintenance and growth. It is hypothesized that this response will manifest itself at the population level as a reduction in growth for a given substrate utilization rate, i.e. a reduction in the apparent biomass yield coefficient. Experimental systems will involve Pseudomonas stutzeri GM-1 as a target organism and two model chemical stressors, benzene and N-ethylmalemide (NEM). Measurements of biomass growth, substrate utilization and oxygen uptake will be interpreted using mathematical models to infer the extent to which the chemical stressor places excess carbon and energy requirements on the metabolic functions. A second type of experiment will explore the ability of a population to adapt to chemical stressors thereby tolerating ongoing perturbations. Broader Impacts:The primary educational component of this project is in the form of senior thesis topics envisioned to be computational rather than experimental. These projects would involve mathematical modeling to explore shifts in community structure and their relation to cellular- and population-level stress response mechanisms. This year-long SGER project will test new hypotheses and generate findings that are critical to the further development of new research in microbial stress responses. Further knowledge gained in this research area will lead to broad insights about microbiological stress response mechanisms and their manifestations at a variety of organizational scales. This information can ultimately be useful in more accurate ecological risk assessments, effective design and operation of biotreatment systems, and development of molecular biosensors for detecting chemical stressors.

0302432 PETERS有许多工程和自然系统的例子，其中该系统的功能依赖于稳定的微生物生物群落。一个很好的例子是工程生物学治疗系统中的活性污泥。异种生物化学物质对这种系统的扰动可能会导致生物胁迫，并随后在微生物群落的结构和功能上转移。在人口水平上表现出来的变化可能包括资源从增长过程中转移，以及该物种的生理或进化适应。社区层面的变化可能包括物种多样性的转变，分解代谢功能的转变以及社区总体耐受性的改变。理解细胞水平对化学压力源与种群和社区水平反应之间的联系的关键在于单个物种的代谢反应。该项目旨在（i）建立方法论来衡量对化学胁迫的代谢反应，以及（ii）关于生长动力学反应对化学胁迫的关键假设。最近的工作表明，氧化化学应激源引起了革兰氏阴性细菌中的谷胱甘肽门控钾外排。预计这种机制将施加能量需求，而不是细胞维持和生长所需的能量需求。假设这种反应将在人群水平上表现为给定底物利用率的生长降低，即降低了明显的生物量收益系数。实验系统将涉及假单胞菌GM-1作为靶向生物和两个模型的化学胁迫，苯和N-乙基甲酰胺（NEM）。生物量生长，底物利用率和氧气摄取的测量将使用数学模型来解释，以推断化学应激源对代谢功能的过量碳和能量需求的程度。第二种实验将探索种群适应化学应激源的能力，从而耐受持续的扰动。更广泛的影响：该项目的主要教育组成部分是以高级论文主题的形式设想为计算，而不是实验性的。这些项目将涉及数学建模，以探索社区结构的转变及其与细胞和人口水平应力反应机制的关系。今年为期一年的SGER项目将检验新的假设，并产生对微生物压力反应新研究至关重要的发现。在该研究领域获得的进一步知识将导致有关微生物应力反应机制及其在各种组织规模上的表现的广泛见解。该信息最终可以在更准确的生态风险评估，生物处理系统的有效设计和操作以及用于检测化学胁迫的分子生物传感器的开发中有用。