Passive Samplers, a Powerful Tool to Detect Viruses and Bacteria in Marine Coastal Areas

The detection of viruses and bacteria which can pose a threat either to shellfish health or shellfish consumers remains difficult. The current detection methods rely on point sampling of water, a method that gives a snapshot of the microorganisms present at the time of sampling. In order to obtain better representativeness of the presence of these microorganisms over time, we have developed passive sampling using the adsorption capacities of polymer membranes. Our objectives here were to assess the feasibility of this methodology for field detection. Different types of membrane were deployed in coastal waters over 2 years and the microorganisms tested using qPCR were: human norovirus (NoV) genogroups (G)I and II, sapovirus, Vibrio spp. and the species Vibrio alginolyticus, V. cholerae, V. vulnificus, and V. parahaemolyticus, OsHV-1 virus, and bacterial markers of fecal contamination. NoV GII, Vibrio spp., and the AllBac general Bacteroidales marker were quantified on the three types of membrane. NoV GII and OsHV-1 viruses followed a seasonal distribution. All membranes were favorable for NoV GII detection, while Zetapor was more adapted for OsHV-1 detection. Nylon was more adapted for detection of Vibrio spp. and the AllBac marker. The quantities of NoV GII, AllBac, and Vibrio spp. recovered on membranes increased with the duration of exposure. This first application of passive sampling in seawater is particularly promising in terms of an early warning system for the prevention of contamination in oyster farming areas and to improve our knowledge on the timing and frequency of disease occurence.

Automated summary

The study developed a passive sampling method using polymer membranes to detect viruses and bacteria in seawater, which proved to be promising for early warning system in oyster farming areas and improving knowledge on disease occurrence timing and frequency. Different membranes showed varying degrees of effectiveness in detecting specific microorganisms, with some showing seasonal distribution patterns.