Analytical validation of a semi-automated methodology for quantitative measurement of SARS-CoV-2 RNA in wastewater collected in northern New England.

Microbiology spectrum
Authors
Keywords
Abstract

Wastewaterbased epidemiology (WBE) can be used to monitor the community presence of infectious disease pathogens of public health concern such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Viral nucleic acid has been detected in the stool of SARS-CoV-2-infected individuals. Asymptomatic SARS-CoV-2 infections make community monitoring difficult without extensive and continuous population screening. In this study, we validated a procedure that includes manual pre-processing, automated SARS-CoV-2 RNA extraction and detection workflows using both reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR) and reverse transcriptase droplet digital PCR (RT-ddPCR). Genomic RNA and calibration materials were used to create known concentrations of viral material to determine the linearity, accuracy, and precision of the wastewater extraction and SARS-CoV-2 RNA detection. Both RT-qPCR and RT-ddPCR perform similarly in all the validation experiments, with a limit of detection of 50 copies/mL. A wastewater sample from a care facility with a known outbreak was assessed for viral content in replicate, and we showed consistent results across both assays. Finally, in a 2-week survey of two New Hampshire cities, we assessed the suitability of our methods for daily surveillance. This paper describes the technical validation of a molecular assay that can be used for long-term monitoring of SARS-CoV-2 in wastewater as a potential tool for community surveillance to assist with public health efforts.IMPORTANCEThis paper describes the technical validation of a molecular assay that can be used for the long-term monitoring of SARS-CoV-2 in wastewater as a potential tool for community surveillance to assist with public health efforts.

Year of Publication
2024
Journal
Microbiology spectrum
Pages
e0112223
Date Published
05/2024
ISSN
2165-0497
DOI
10.1128/spectrum.01122-23
PubMed ID
38747589
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