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.

[03:24 . 32]彼得斯有许多工程系统和自然系统的例子，其中系统的功能依赖于稳定的微生物生物群落。工程生物处理系统中的活性污泥就是一个很好的例子。外来化学物质对这些系统的扰动可能导致生物应激和随后的微生物群落结构和功能的变化。在种群水平上表现出来的变化可能包括资源从生长过程中转移，以及物种的生理或进化适应。群落水平的变化可能包括物种多样性的变化、分解代谢功能的变化和群落整体抗逆性的变化。理解细胞水平对化学应激源的反应与种群和群落水平的反应之间的联系的关键在于个体物种的代谢反应。该项目旨在(i)建立测量化学应激源代谢反应的方法，以及（ii）测试关于化学应激源生长动力学反应的关键假设。最近的研究表明，氧化化学应激源在革兰氏阴性菌中引起谷胱甘肽门控钾外排（GGKE）应激反应。这种机制预计会增加超出细胞维持和生长正常所需的能量需求。据推测，这种反应将在种群水平上表现为对给定底物利用率的生长减少，即表观生物量产量系数的减少。实验系统将包括假单胞菌stutzeri GM-1作为目标生物和两种模型化学应激源，苯和n -乙基马来酰胺（NEM）。生物量增长、基质利用和氧气摄取的测量将使用数学模型进行解释，以推断化学应激源对代谢功能施加过量碳和能量需求的程度。第二种类型的实验将探索种群适应化学压力源的能力，从而容忍持续的扰动。更广泛的影响：这个项目的主要教育组成部分是以高级论文主题的形式设想的计算而不是实验。这些项目将涉及数学建模，以探索群落结构的变化及其与细胞和种群水平应激反应机制的关系。这个为期一年的SGER项目将测试新的假设，并产生对微生物应激反应新研究的进一步发展至关重要的发现。在该研究领域获得的进一步知识将导致对微生物应激反应机制及其在各种组织尺度上的表现的广泛见解。这些信息最终可用于更准确的生态风险评估、有效的生物处理系统设计和操作，以及用于检测化学应激源的分子生物传感器的开发。