基于微流控技术的水环境病原体微生物污染的监测与预警研究

水环境不仅承担供水任务，还是经济活动的重要载体，其生物安全对人类健康和经济发展具有重大影响。其中，对其生物污染开展全方位、快速、实时监测，是保障其生物安全的根本，是构建国家生物安全体系的重要环节。然而，当前对水环境生物污染监测还存在较大不足。例如，目前国际上绝大多数以粪便指示菌为指标对水体病原体微生物污染进行监测与评估，存在较大不确定性和单一性，亟需建立全方位的监测手段和评估体系。基于此，本项目聚焦厦门海域，通过研发新型微流控病原体检测芯片，建立一种新型的监测手段，对厦门海域病原体进行全方位筛查，有效解决我国亚热带海域缺少病原体微生物数据库的难题，并突破海洋病原体微生物快速准确检测、时间和空间序列连续监测、灾害快速准确溯源等关键技术和科学问题。同时，在建立病原体微生物数据库的基础上，运用机器学习方法构建环境风险评估模型和预警系统，应用于病原体污染风险评估，为风险管理和灾害防治提供科学依据。

Water environment not only supports daily water supply but is also an important carrier of economic activities. The biological safety of water, therefore, has an incredible impact on economic development and human activities. It is no doubt that comprehensive monitoring, real-time early warning, and prevention methods will play an essential role in ensuring biological safety of water and establishing national biosafety regulatory systems. Currently, fecal indicator bacteria (FIB) are commonly used to monitor and assess water quality. However, studies find that FIB suffers great limitations, for example, uncertainty and underrepresented, to protect human health. Therefore, it is urgent to establish a complete method to monitor and assess water quality. Based on this situation, we will develop a novel, simultaneous microfluidic multiple-pathogen detection chip (MPDC) and establish a new method to monitor and assess water quality. With the help of MPDC the harmful microorganisms database in subtropical water in china will be established by fully screening pathogens in coastal water around Xiamen island. The key technical and scientific issues related to harmful microorganisms in the coastal water, for example, “who they are, how many they are, where they come from, how dangerous they are”, will be also broken out through rapidly and accurately detecting microorganisms, continuously and spatiotemporally monitoring, and speedily and properly tracing disaster sources. At the same time, based on the harmful microorganisms database obtained from this project, machine learning will be implemented to build urgently needed environmental risk assessment models and early warning systems, which would successfully propose feasible risk management and disaster prevention and benefit socio-economics and human health.