Reproducibility and sensitivity of 36 methods to quantify the SARS-CoV-2 genetic signal in raw wastewater: findings from an interlaboratory methods evaluation in the U.S.
Environ Sci (Camb)
; 7: 504-520, 2021 Jan 20.
Article
en En
| MEDLINE
| ID: mdl-34017594
ABSTRACT
In response to COVID-19, the international water community rapidly developed methods to quantify the SARS-CoV-2 genetic signal in untreated wastewater. Wastewater surveillance using such methods has the potential to complement clinical testing in assessing community health. This interlaboratory assessment evaluated the reproducibility and sensitivity of 36 standard operating procedures (SOPs), divided into eight method groups based on sample concentration approach and whether solids were removed. Two raw wastewater samples were collected in August 2020, amended with a matrix spike (betacoronavirus OC43), and distributed to 32 laboratories across the U.S. Replicate samples analyzed in accordance with the project's quality assurance plan showed high reproducibility across the 36 SOPs 80% of the recovery-corrected results fell within a band of ±1.15 log10 genome copies per L with higher reproducibility observed within a single SOP (standard deviation of 0.13 log10). The inclusion of a solids removal step and the selection of a concentration method did not show a clear, systematic impact on the recovery-corrected results. Other methodological variations (e.g., pasteurization, primer set selection, and use of RT-qPCR or RT-dPCR platforms) generally resulted in small differences compared to other sources of variability. These findings suggest that a variety of methods are capable of producing reproducible results, though the same SOP or laboratory should be selected to track SARS-CoV-2 trends at a given facility. The methods showed a 7 log10 range of recovery efficiency and limit of detection highlighting the importance of recovery correction and the need to consider method sensitivity when selecting methods for wastewater surveillance.
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Banco de datos:
MEDLINE
Tipo de estudio:
Diagnostic_studies
Idioma:
En
Año:
2021
Tipo del documento:
Article