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Droplet digital RT-PCR to detect SARS-CoV-2 signature mutations of variants of concern in wastewater

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“Wastewater surveillance has shown to be a valuable and efficient tool to obtain information about the trends of COVID-19 in the community. Since the recent emergence of new variants, associated with increased transmissibility and/or antibody escape (variants of concern), there is an urgent need for methods that enable specific and timely detection and quantification of the occurrence of these variants in the community. In this study, we demonstrate the use of RT-ddPCR on wastewater samples for specific detection of mutation N501Y. This assay enabled simultaneous enumeration of lineage B.1.351 (containing the 501Y mutation) and Wild Type (WT, containing 501N) SARS-CoV-2 RNA. Detection of N501Y was possible in samples with mixtures of WT with low proportions of B.1.351 (0.5%) and could accurately determine the proportion of N501Y and WT in mixtures of SARS-CoV-2 RNA. The application to raw sewage samples from the cities of Amsterdam and Utrecht demonstrated that this method can be applied to wastewater samples. The emergence of N501Y in Amsterdam and Utrecht wastewater aligned with the emergence of B.1.1.7 as causative agent of COVID-19 in the Netherlands, indicating that RT-ddPCR of wastewater samples can be used to monitor the emergence of the N501Y mutation in the community. It also indicates that RT-ddPCR could be used for sensitive and accurate monitoring of current (like K417N, K417T, E484K, L452R) or future mutations present in SARS-CoV-2 variants of concern. Monitoring these mutations can be used to obtain insight in the introduction and spread of VOC and support public health decision-making regarding measures to limit viral spread or allocation of testing or vaccination.”

(Citation: Heijnen, L., Elsinga, G.S., de Graaf, M., et.al. – Droplet digital RT-PCR to detect SARS-CoV-2 signature mutations of variants of concern in wastewater – Science of the Total Environment 799(2021)art. no. 149456 – DOI: 10.1016/j.scitotenv.2021.149456 – (Open Access))

This article is available under the Creative Commons CC-BY-NC-ND license
© 2021 The Authors. Published by Elsevier B.V.

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