Identification of SARS-CoV-2 variants in wastewater using targeted amplicon sequencing during a low COVID-19 prevalence period in Japan.

ABSTRACT

Wastewater-based epidemiology is expected to be able to identify SARS-CoV-2 variants at an early stage via next-generation sequencing. In the present study, we developed a highly sensitive amplicon sequencing method targeting the spike gene of SARS-CoV-2, which allows for sequencing viral genomes from wastewater containing a low amount of virus. Primers were designed to amplify a relatively long region (599 bp) around the receptor-binding domain in the SARS-CoV-2 spike gene, which could distinguish initial major variants of concern. To validate the methodology, we retrospectively analyzed wastewater samples collected from a septic tank installed in a COVID-19 quarantine facility between October and December 2020. The relative abundance of D614G mutant in SARS-CoV-2 genomes in the facility wastewater increased from 47.5 % to 83.1 % during the study period. The N501Y mutant, which is the characteristic mutation of the Alpha-like strain, was detected from wastewater collected on December 24, 2020, which agreed with the fact that a patient infected with the Alpha-like strain was quarantined in the facility on this date. We then analyzed archived municipal wastewater samples collected between November 2020 and January 2021 that contained low SARS-CoV-2 concentrations ranging from 0.23 to 0.43 copies/qPCR reaction (corresponding to 3.30 to 4.15 log10 copies/L). The targeted amplicon sequencing revealed that the Alpha-like variant with D614G and N501Y mutations was present in municipal wastewater collected on December 4, 2020 and later, suggesting that the variant had already spread in the community before its first clinical confirmation in Japan on December 25, 2020. These results demonstrate that targeted amplicon sequencing of wastewater samples is a powerful surveillance tool applicable to low COVID-19 prevalence periods and may contribute to the early detection of emerging variants.