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

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，而不需要化学消毒剂。生物过滤的采用受到不期望的微生物将被释放到饮用水中的担忧的阻碍。克服这种担忧将有助于为这项技术的广泛采用铺平道路。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。这种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，以丰富有益的微生物。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。学术界和工业界的合作将有助于加快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终点指导的，但目前的生物过滤器控制方法缺乏管理微生物群落所需的细微差别。考虑到这种缺乏控制，这是毫不奇怪的，有很少或没有知识的生物过滤器微生物如何有助于生物过滤器的性能。这种知识差距加上对生物过滤器微生物在配水系统中接种的担忧，一直是该技术大规模工业化采用的主要障碍。为了克服这一障碍，本项目将开发新的生态基因组框架（EGF）来控制生物过滤器微生物群落。该项目的重点是使用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，微生物的消毒抗性与生物过滤器微生物中的氮物种可用性和由此产生的遗传应激反应有关。该项目将通过实验测试EGF预测1）建立氮物种可用性和生物过滤器微生物产生的氮胁迫反应之间的关系，2）定量地将氮胁迫反应和消毒抗性联系起来，3）优化生物过滤器中的氮物种可用性，以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在生物过滤器操作中的实用性的概念证明，该生物过滤器操作由具有生产合作记录的学术和工业研究人员领导，这一奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查评估的支持的搜索.

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.