Development and Validation of the Skimmed Milk Pellet Extraction Protocol for SARS-CoV-2 Wastewater Surveillance.

Wastewater surveillance for SARS-CoV-2 may serve as a useful source of data for public health departments as the virus is shed in the stool of infected individuals. However, for wastewater data to be actionable, wastewater must be collected, concentrated, and analyzed in a timely manner. This manuscript presents modifications on a skimmed milk concentration protocol to reduce processing time, increase the number of samples that can be processed at once, and enable use in resource-limited settings. Wastewater seeded with Human coronavirus OC43 (OC43) was concentrated using a skimmed milk flocculation protocol, and then pellets were directly extracted with the QIAamp Viral RNA Mini kit. This protocol has a higher average effective volume assayed (6.35 mL) than skimmed milk concentration methods, with and without Vertrel XF™, which involve resuspension of the pellets in PBS extraction prior to nucleic acid extraction (1.28 mL, 1.44 mL, respectively). OC43 was selected as a recovery control organism because both it and SARS-CoV-2 are enveloped respiratory viruses that primarily infect humans resulting in respiratory symptoms. The OC43 percent recovery for the direct extraction protocol (3.4%) is comparable to that of skimmed milk concentration with and without Vertrel XF™ extraction (4.0%, 2.6%, respectively). When comparing SARS-CoV-2 detection using McNemar's chi-square test, the pellet extraction method is not statistically different from skimmed milk concentration, with and without Vertrel XF™ extraction. This suggests that the method performs equally as well as existing methods. Added benefits include reduced time spent per sample and the ability to process more samples at a single time. Direct extraction of skimmed milk pellets is a viable method for quick turnaround of wastewater data for public health interventions.

A comparison of SARS-CoV-2 wastewater concentration methods for environmental surveillance.

Wastewater1 surveillance of SARS-CoV-2 may be a useful supplement to clinical surveillance as it is shed in feces, there are many asymptomatic cases, and diagnostic testing can have capacity limitations and extended time to results. Although numerous studies have utilized wastewater surveillance for SARS-CoV-2, the methods used were developed and/or standardized for other pathogens. This study evaluates multiple methods for concentration and recovery of SARS-CoV-2 and seeded human coronavirus OC43 from municipal primary wastewater and/or sludge from the Greater Seattle Area (March-July 2020). Methods evaluated include the bag-mediated filtration system (BMFS), with and without Vertrel™ extraction, skimmed milk flocculation, with and without Vertrel™ extraction, polyethylene glycol (PEG) precipitation, ultrafiltration, and sludge extraction. Total RNA was extracted from wastewater concentrates and analyzed for SARS-CoV-2 and OC43 with RT-qPCR. Skimmed milk flocculation without Vertrel™ extraction performed consistently over time and between treatment plants in Seattle-area wastewater with the lowest average OC43 Cq value and smallest variability (24.3; 95% CI: 23.8-24.9), most frequent SARS-CoV-2 detection (48.8% of sampling events), and highest average OC43 percent recovery (9.1%; 95% CI: 6.2-11.9%). Skimmed milk flocculation is also beneficial because it is feasible in low-resource settings. While the BMFS had the highest average volume assayed of 11.9 mL (95% CI: 10.7-13.1 mL), the average OC43 percent recovery was low (0.7%; 95% CI: 0.4-1.0%). Ultrafiltration and PEG precipitation had low average OC43 percent recoveries of 1.0% (95% CI: 0.5-1.6%) and 3.2% (95% CI: 1.3-5.1%), respectively. The slopes and efficiency for the SARS-CoV-2 standard curves were not consistent over time, confirming the need to include a standard curve each run rather than using a single curve for multiple plates. Results suggest that the concentration and detection methods used must be validated for the specific water matrix using a recovery control to assess performance over time.