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

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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.