Great Lakes Recreational Water Security: Microbial community characterization, source tracking and remediation through meta-genomics

五大湖休闲用水安全：通过元基因组学进行微生物群落表征、源头追踪和修复

• 批准号: 479134-2015
• 负责人: Heath, Daniel
• 金额: $ 13.66万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=599881
• 关键词: Great; Lakes; Recreational; Water; Security

Microbial (bacterial and algal) contamination in recreational and drinking water is of particular concern as it can directly affect human health and have large economic impacts (e.g., beach closures, fisheries losses, water treatment costs, etc.). In the Great Lakes, microbial contamination has increased substantially, with beach closures in the Essex region at 4X previous levels. Additionally, dangerous levels of microcystin, a toxin produced by algal blooms, have been recorded in Lake Erie. Furthermore, preliminary data indicate that current monitoring for E. coli (human pathogen indicator) may generate false positive and negative results. It is thus critical that reliable, rapid and predictive methods are developed to characterize potentially hazardous microbial contaminants. This proposal uses an integrated approach to identify, predict and treat harmful microbial outbreaks to ensure water security. Specifically, Lake St. Clair and western Lake Erie will be used to develop and apply genomics-based assays for aquatic microbial contaminants. Our proposal consists of three Themes: 1) Microbial Community Characterization (Identification): We will use Next Generation sequencing to identify the bacterial and algal communities over time and space. 2) Microbial Community Dynamics (Prediction): We will use hydrodynamic modelling, genomics-based source tracking and biophysical data to develop predictive models to provide managers an early warning of harmful microbial outbreaks. 3) Microbial Contamination Remediation (Treatment): Using a novel approach for remediation of microbial contamination, we will identify microbial contamination sources and our predictive models will generate a decision making tree for specific remediation actions based on calculated risk levels. Finally, we will work with Industry partners to develop novel "on site" treatment technologies. Our integrated approach will fill a pressing need for novel solutions for microbial water security in large lake systems and result in a suite of tools that could be applied seamlessly around the Great Lakes, across Canada and around the world. Our goal is to use effective partnerships to develop novel technology to address pathogen and toxin threats in our water supplies.

娱乐用水和饮用水中的微生物（细菌和藻类）污染特别令人关注，因为它可以直接影响人类健康并具有巨大的经济影响（例如，海滩关闭、渔业损失、水处理费用等）。在五大湖，微生物污染大幅增加，埃塞克斯地区的海滩关闭率达到了以前的4倍。此外，伊利湖中记录了藻类大量繁殖产生的毒素微囊藻毒素的危险水平。此外，初步数据表明，目前的监测E。大肠杆菌（人类病原体指示剂）可能会产生假阳性和假阴性结果。因此，开发可靠、快速和预测性的方法来表征潜在的有害微生物污染物至关重要。该提案采用综合方法来识别、预测和处理有害微生物爆发，以确保水安全。具体而言，圣克莱尔湖和西部伊利湖将用于开发和应用基于基因组学的水生微生物污染物检测。我们的提案包括三个主题：1）微生物群落表征（鉴定）：我们将使用下一代测序来鉴定细菌和藻类群落的时间和空间。2)微生物群落动态（预测）：我们将使用流体动力学建模，基于基因组学的源跟踪和生物物理数据来开发预测模型，为管理人员提供有害微生物爆发的早期预警。3)微生物污染修复（处理）：使用一种新的方法来修复微生物污染，我们将识别微生物污染源，我们的预测模型将根据计算的风险水平为特定的修复行动生成决策树。最后，我们将与行业合作伙伴共同开发新型的“现场”处理技术。我们的综合方法将满足对大型湖泊系统微生物水安全新解决方案的迫切需求，并产生一套可在五大湖、加拿大和世界各地无缝应用的工具。我们的目标是利用有效的伙伴关系开发新技术，以解决我们供水中的病原体和毒素威胁。