Abstract
Wastewater-based epidemiology (WBE) is a promising approach for monitoring the spread of SARS-CoV-2 within communities. Although qPCR-based WBE is powerful in that it allows quick and highly sensitive detection of this virus, it can provide limited information about which variants are responsible for the overall increase or decrease of this virus in sewage, and this hinders accurate risk assessments. To resolve this problem, we developed a next generation sequencing (NGS)-based method to determine the identity and composition of individual SARS-CoV-2 variants in wastewater samples. Combination and optimization of targeted amplicon-sequencing and nested PCR allowed detection of each variant with sensitivity comparable to that of qPCR. In addition, by targeting the receptor binding domain (RBD) of the S protein, which has mutations informative for variant classification, we could discriminate most variants of concern (VOC) and even sublineages of Omicron (BA.1, BA.2, BA.4/5, BA.2.75, BQ.1.1 and XBB.1). Focusing on a limited domain has a benefit of decreasing the sequencing reads. We applied this method to wastewater samples collected from a wastewater treatment plant in Kyoto city throughout 13 months (from January 2021 to February 2022) and successfully identified lineages of wild-type, alpha, delta, omicron BA.1 and BA.2 as well as their compositions in the samples. The transition of these variants was in good agreement with the epidemic situation reported in Kyoto city during that period based on clinical testing. These data indicate that our NGS-based method is useful for detecting and tracking emerging variants of SARS-CoV-2 in sewage samples. Coupled with the advantages of WBE, this method has the potential to serve as an efficient and low cost means for the community risk assessment of SARS-CoV-2 infection.