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

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.

Wastewater-based prediction of COVID-19 cases using a highly sensitive SARS-CoV-2 RNA detection method combined with mathematical modeling.

Wastewater-based epidemiology (WBE) has the potential to predict COVID-19 cases; however, reliable methods for tracking SARS-CoV-2 RNA concentrations (CRNA) in wastewater are lacking. In the present study, we developed a highly sensitive method (EPISENS-M) employing adsorption-extraction, followed by one-step RT-Preamp and qPCR. The EPISENS-M allowed SARS-CoV-2 RNA detection from wastewater at 50 % detection rate when newly reported COVID-19 cases exceed 0.69/100,000 inhabitants in a sewer catchment. Using the EPISENS-M, a longitudinal WBE study was conducted between 28 May 2020 and 16 June 2022 in Sapporo City, Japan, revealing a strong correlation (Pearson's r = 0.94) between CRNA and the newly COVID-19 cases reported by intensive clinical surveillance. Based on this dataset, a mathematical model was developed based on viral shedding dynamics to estimate the newly reported cases using CRNA data and recent clinical data prior to sampling day. This developed model succeeded in predicting the cumulative number of newly reported cases after 5 days of sampling day within a factor of √2 and 2 with a precision of 36 % (16/44) and 64 % (28/44), respectively. By applying this model framework, another estimation mode was developed without the recent clinical data, which successfully predicted the number of COVID-19 cases for the succeeding 5 days within a factor of √2 and 2 with a precision of 39 % (17/44) and 66 % (29/44), respectively. These results demonstrated that the EPISENS-M method combined with the mathematical model can be a powerful tool for predicting COVID-19 cases, especially in the absence of intensive clinical surveillance.

Impact of the COVID-19 pandemic on the prevalence of influenza A and respiratory syncytial viruses elucidated by wastewater-based epidemiology.

Since the COVID-19 pandemic, a decrease in the prevalence of Influenza A virus (IAV) and respiratory syncytial virus (RSV) has been suggested by clinical surveillance. However, there may be potential biases in obtaining an accurate overview of infectious diseases in a community. To elucidate the impact of the COVID-19 on the prevalence of IAV and RSV, we quantified IAV and RSV RNA in wastewater collected from three wastewater treatment plants (WWTPs) in Sapporo, Japan, between October 2018 and January 2023, using highly sensitive EPISENS™ method. From October 2018 to April 2020, the IAV M gene concentrations were positively correlated with the confirmed cases in the corresponding area (Spearman's r = 0.61). Subtype-specific HA genes of IAV were also detected, and their concentrations showed trends that were consistent with clinically reported cases. RSV A and B serotypes were also detected in wastewater, and their concentrations were positively correlated with the confirmed clinical cases (Spearman's r = 0.36-0.52). The detection ratios of IAV and RSV in wastewater decreased from 66.7 % (22/33) and 42.4 % (14/33) to 4.56 % (12/263) and 32.7 % (86/263), respectively in the city after the COVID-19 prevalence. The present study demonstrates the potential usefulness of wastewater-based epidemiology combined with the preservation of wastewater (wastewater banking) as a tool for better management of respiratory viral diseases.

The Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids (EPISENS-S): A rapid and cost-effective SARS-CoV-2 RNA detection method for routine wastewater surveillance.

Wastewater-based epidemiology has attracted attention as a COVID-19 surveillance tool. Here, we developed a practical method for detecting SARS-CoV-2 RNA in wastewater (the EPISENS-S method), which employs direct RNA extraction from wastewater pellets formed via low-speed centrifugation. The subsequent multiplex one-step RT-preamplification reaction with forward and reverse primers for SARS-CoV-2 and a reverse primer only for pepper mild mottle virus (PMMoV) allowed for qPCR quantification of the targets with different abundances in wastewater from the RT-preamplification product. The detection sensitivity of the method was evaluated using wastewater samples seeded with heat-inactivated SARS-CoV-2 in concentrations of 2.11 × 103 to 2.11 × 106 copies/L. The results demonstrated that the sensitivity of the EPISENS-S method was two orders of magnitude higher than that of the conventional method (PEG precipitation, followed by regular RT-qPCR; PEG-QVR-qPCR). A total of 37 untreated wastewater samples collected from two wastewater treatment plants in Sapporo, Japan when 1.6 to 18 new daily reported cases per 100,000 people were reported in the city (March 4 to July 8, 2021), were examined using the EPISENS-S method to confirm its applicability to municipal wastewater. SARS-CoV-2 RNA was quantified in 92 % (34/37) of the samples via the EPISENS-S method, whereas none of the samples (0/37) was quantifiable via the PEG-QVR-qPCR method. The PMMoV concentrations measured by the EPISENS-S method ranged from 2.60 × 106 to 1.90 × 108 copies/L, and the SARS-CoV-2 RNA concentrations normalized by PMMoV ranged from 5.71 × 10-6 to 9.51 × 10-4 . The long-term trend of normalized SARS-CoV-2 RNA concentration in wastewater was consistent with that of confirmed COVID-19 cases in the city. These results demonstrate that the EPISENS-S method is highly sensitive and suitable for routine COVID-19 wastewater surveillance.

The detectability and removal efficiency of SARS-CoV-2 in a large-scale septic tank of a COVID-19 quarantine facility in Japan.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to be present in sewage, and wastewater-based epidemiology has attracted much attention. However, the physical partitioning of SARS-CoV-2 in wastewater and the removal efficiency of treatment systems require further investigation. This study aimed to investigate the detectability and physical partitioning of SARS-CoV-2 in wastewater and assess its removal in a large-scale septic tank employing anaerobic, anoxic, and oxic processes in a sequential batch reactor, which was installed in a coronavirus disease 2019 (COVID-19) quarantine facility. The amount of SARS-CoV-2 RNA in wastewater was determined with polyethylene glycol (PEG) precipitation followed by quantitative polymerase chain reaction (qPCR), and the association of SARS-CoV-2 with wastewater solids was evaluated by the effect of filtration prior to PEG precipitation (pre-filtration). The amount of SARS-CoV-2 RNA detected from pre-filtered samples was substantially lower than that of samples without pre-filtration. These results suggest that most SARS-CoV-2 particles in wastewater are associated with the suspended solids excluded by pre-filtration. The removal efficiency of SARS-CoV-2 in the septic tank was evaluated based on the SARS-CoV-2 RNA concentrations in untreated and treated wastewater, which was determined by the detection method optimized in this study. Escherichia coli and pepper mild mottle virus (PMMoV) were also quantified to validate the wastewater treatment system's performance. The mean log10 reduction values of SARS-CoV-2, E. coli, and PMMoV were 2.47 (range, 2.25-2.68), 2.81 (range, 2.45-3.18), and 0.66 (range, 0.61-0.70), respectively, demonstrating that SARS-CoV-2 removal by the wastewater treatment system was comparable to or better than the removal of fecal indicators. These results suggest that SARS-CoV-2 can be readily removed by the septic tank. This is the first study to determine the removal efficiency of SARS-CoV-2 in a facility-level sequencing batch activated sludge system.