Monitoring SARS-CoV-2 in sewage: Toward sentinels with analytical accuracy

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemia has been one of the most difficult challenges humankind has recently faced. Wastewater-based epidemiology has emerged as a tool for surveillance and mitigation of potential viral outbreaks, circumventing biases introduced by clinical patient testing. Due to the situation urgency, protocols followed for isolating viral RNA from sewage were not adapted for such sample matrices. In parallel to their implementation for fast collection of data to sustain surveillance and mitigation decisions, molecular protocols need to be harmonized to deliver accurate, reproducible, and comparable analytical outputs. Here we studied analytical variabilities linked to viral RNA isolation methods from sewage. Three different influent wastewater volumes were used to assess the effects of filtered volumes (50, 100 or 500 mL) for capturing viral particles. Three different concentration strategies were tested: electronegative membranes, polyethersulfone membranes, and anion-exchange diethylaminoethyl cellulose columns. To compare the number of viral particles, different RNA isolation methods (column-based vs. magnetic beads) were compared. The effect of extra RNA purification steps and different RT-qPCR strategies (one step vs. two-step) were also evaluated. Results showed that the combination of 500 mL filtration volume through electronegative membranes and without multiple RNA purification steps (using column-based RNA purification) using two-step RT-qPCR avoided false negatives when basal viral load in sewage are present and yielded more consistent results during the surveillance done during the second-wave in Delft (The Hague area, The Netherlands). By paving the way for standardization of methods for the sampling, concentration and molecular detection of SARS-CoV-2 viruses from sewage, these findings can help water and health surveillance authorities to use and trust results coming from wastewater based epidemiology studies in order to anticipate SARS-CoV-2 outbreaks.