GOALI: Developing an Eco-Genomic Framework for Biofilter Operation.

目标：开发生物过滤器操作的生态基因组框架。

• 批准号: 2203731
• 负责人: Ameet Pinto
• 金额: $ 34.02万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2203731&HistoricalAwards=false
• 关键词: GOALI; Developing; Eco; Genomic; Framework

Biofilters use naturally-occurring microorganisms to filter and remove pollutants in drinking water without the need for disinfectant chemicals. Adoption of biofiltration is hindered by concerns that undesirable microorganisms will be released into the drinking water. Overcoming this concern would help pave the way for wide-scale adoption of this technology. The goal of this project is to develop a novel framework to control the biofilter microbial community. Such control will allow management of biofilter performance. To achieve this goal, the research team will perform laboratory and pilot-scale experiments using state-of-the-art genomic techniques to enrich beneficial microorganisms. The project team includes experts in drinking water treatment, biofiltration, and microbial ecology. The academic and industrial collaboration will help speed the transition of research to full-scale industrial implementation. Biofilter operation is guided by chemical and microbiological endpoints, yet current biofilter control approaches lack the nuance necessary for managing microbial communities. Considering this lack of control, it is no surprise that there is little to no knowledge of how biofilter microbes contribute to biofilter performance. This knowledge gap coupled with concerns about the seeding of the water distribution system with biofilter microbes has been a major stumbling block for the wide-scale industrial adoption of this technology. To overcome this barrier, this project will develop the novel Eco-Genomic Framework (EGF) for controlling the biofilter microbial community. This project focusses on using the EGF to tailor the biofilter microbial community to enhance post-filtration disinfection efficacy while maintaining biofilter performance. Preliminary EGF research results suggest that microbial disinfection resistance is associated with nitrogen species availability and resultant genetic stress response in biofilter microorganisms. This project will experimentally test EGF predictions 1) to establish a relationship between nitrogen species availability and nitrogen stress response exerted by biofilter microbes, 2) quantitatively link nitrogen stress response and disinfection resistance, and 3) optimize nitrogen species availability in the biofilter to maximize disinfection efficacy while minimizing potential deleterious impacts. These objectives will be accomplished through laboratory- and pilot-scale experiments coupled with state-of-the-art molecular, bioinformatics, and statistical approaches. The outcomes of this project will serve as proof of concept for the utility of the novel EGF for biofilter operation led by academic and industrial researchers with a track record of productive collaboration, thus increasing the likelihood of successful EGF development and industrial deployment.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.

生物过滤器使用天然存在的微生物来过滤和去除饮用水中的污染物，而不需要消毒化学品。由于担心有害的微生物会被释放到饮用水中，生物过滤的采用受到了阻碍。克服这种担忧将有助于为这项技术的大规模采用铺平道路。本项目的目标是开发一种新的框架来控制生物过滤器的微生物群落。这样的控制将允许管理生物过滤器的性能。为了实现这一目标，研究小组将使用最先进的基因组技术进行实验室和中试规模的实验，以丰富有益微生物。项目团队包括饮用水处理、生物过滤和微生物生态学方面的专家。学术和工业合作将有助于加速研究向全面工业实施的过渡。生物过滤器的操作是由化学和微生物端点指导的，但目前的生物过滤器控制方法缺乏管理微生物群落所必需的细微差别。考虑到这种缺乏控制的情况，对于生物过滤器微生物如何促进生物过滤器的性能知之甚少也就不足为奇了。这种知识差距加上对生物过滤微生物在配水系统中播种的担忧，一直是该技术大规模工业应用的主要障碍。为了克服这一障碍，该项目将开发新的生态基因组框架（EGF）来控制生物过滤器的微生物群落。本项目的重点是使用EGF来定制生物过滤器的微生物群落，以提高过滤后的消毒效果，同时保持生物过滤器的性能。EGF的初步研究结果表明，微生物消毒抗性与生物过滤器微生物的氮种有效性和由此产生的遗传应激反应有关。本项目将对EGF预测进行实验验证：1)建立生物过滤器微生物对氮胁迫反应与氮可利用性之间的关系；2)定量联系氮胁迫反应与消毒抗性；3)优化生物过滤器中氮可利用性，最大限度地提高消毒效果，同时最大限度地减少潜在的有害影响。这些目标将通过实验室和中试规模的实验，结合最先进的分子、生物信息学和统计方法来实现。该项目的成果将作为新型EGF用于生物过滤器操作的概念证明，由学术和工业研究人员领导，具有富有成效的合作记录，从而增加了EGF成功开发和工业部署的可能性。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。