COLITREND: Monitoring E. COLI dynamics at high temporal resolution in Canadian drinking water supplies using autonomous online measurement technology

通过培养检测粪便指示菌大肠杆菌已成为饮用水水源地微生物质量常规监测的基准。然而，该方法至少需要18-24小时才能提供大肠杆菌计数，这使得在微生物危害导致超过监管阈值的情况下无法快速做出具有成本效益的决定。最近，已经开发了新的技术来简化和加速水中的大肠杆菌检测。他们自动收集并以高精度测量B-D-葡萄糖苷酶活性，这是一种大肠杆菌特有的酶，不需要培养。结果会在用户的计算机或智能手机上实时传递给用户。在这个项目中，我们的目标是在加拿大多个饮用水处理厂实施这项新颖和创新的技术，以更好地评估它们的进水口对粪便污染的脆弱性。这些设备将以精细的时间分辨率测量大肠杆菌的动态，以识别、表征和预测大肠杆菌的峰值浓度，并通过基于过程的建模阐明当地水文气候学和峰值污染事件之间的联系。对于选定的地点和时段，将描述病原体的发生，以了解与测量相关的微生物风险。由于这些新技术提供的荧光单位不同于通过培养获得的经典计数，该项目的主要任务将是将产生的信号与依赖于培养但也不依赖于培养的方法(如实时PCR)产生的信号进行比较。更好地了解这些技术提供的信号，是在早期预警系统中实施这项技术以进行有效水质监测或作为受管制微生物指标的改进替代办法的必要先决条件。为利用高频监测结果制定一个统计和建模框架，将使水资源管理者和监管者能够改进监测、风险评估和决策。该项目将与艾伯塔省和魁北克省的产业合作伙伴合作，培训7名高素质人才。

Detection of the fecal indicator bacterium Escherichia coli by culture has been the benchmark for routine monitoring of microbiological quality in drinking water sources. However, the method requires a minimum of 18-24 hours to deliver E. coli counts, which makes it impossible to take rapid and cost-effective decisions in case of microbial hazards that lead to regulatory threshold exceedances. Recently, new technologies have been developed to streamline and accelerate E. coli detection in water. They autonomously collect and measure at high precision ß-D-glucoronidase activity, an enzyme specific to E. coli, without the need for cultivation. Results are delivered in real time to the user on its computer or smartphone. In this project, we aim at implementing the novel and innovative technology at multiple Canadian drinking water treatment plants to better assess the vulnerability of their intakes to fecal pollution. Devices will measure E. coli dynamics at fine temporal resolution to identify, characterize and predict E. coli peak concentrations and elucidate the association between local hydro-climatology and peak pollution events through process-based modelling. For selected sites and periods, the occurrence of pathogens will be described to understand the microbial risk associated with measurements. As these new technologies provide fluorescence units that are different from the classic counts obtained by culture, a major task of this project will be to compare signals to those generated by culture-dependent but also culture-independent methods such as real time PCR. A better understanding of the signals provided by these technologies is an essential pre-requisite to the implementation of this technology in early warning systems for efficient water quality monitoring or as an improved alternative to regulated microbial indicators. The development of a statistical and modelling framework for the exploitation of the high-frequency monitoring results will enable improved monitoring, risk assessment and decision-making by water managers and regulators. This project will train 7 highly qualified personnel in collaboration with industrial partners from Alberta and Québec.