SARS-CoV-2 variant detection at a university dormitory using wastewater genomic tools.
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ABSTRACT:
SUBMITTER: Vo V
PROVIDER: S-EPMC8421076 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Effectively monitoring the spread of SARS-CoV-2 variants is essential to efforts to counter the ongoing pandemic. Wastewater monitoring of SARS-CoV-2 RNA has proven an effective and efficient technique to approximate COVID-19 case rates in the population. Predicting variant abundances from wastewater, however, is technically challenging. Here we show that by sequencing SARS-CoV-2 RNA in wastewater and applying computational techniques initially used for RNA-Seq quantification, we can estimate the abundance of variants in wastewater samples. We show by sequencing samples from wastewater and clinical isolates in Connecticut U.S.A. between January and April 2021 that the temporal dynamics of variant strains broadly correspond. We further show that this technique can be used with other wastewater sequencing techniques by expanding to samples taken across the United States in a similar timeframe. We find high variability in signal among individual samples, and limited ability to detect the presence of variants with clinical frequencies <10%; nevertheless, the overall trends match what we observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in variant prevalence in situations where clinical sequencing is unavailable or impractical.
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Project description:The University of South Carolina (UofSC) was among the first universities to include building-level wastewater surveillance of SARS-CoV-2 to complement clinical testing during its reopening in the Fall 2020 semester. In the Spring 2021 semester, 24h composite wastewater samples were collected twice per week from 10 residence halls and the on-campus student isolation and quarantine building. The isolation and quarantine building served as a positive control site. The wastewater was analyzed using RT-ddPCR for the quantification of nucleocapsid genes (N1 and N2) to identify viral transmission trends within residence halls. Log10 SARS-CoV-2 RNA concentrations were compared to both new clinical cases identified in the days following wastewater collection and recovered cases returning to sites during the days preceding sample collection to test temporal and spatial associations. There was a statistically significant positive relationship between the number of cases reported from the sites during the seven-day period following wastewater sampling and the log10 viral RNA copies/L (overall IRR 1.08 (1.02, 1.16) p-value 0.0126). Additionally, a statistically significant positive relationship was identified between the number of cases returning to the residence halls after completing isolation during the seven-day period preceding wastewater sampling and the log10 viral RNA copies/L (overall 1.09 (1.01, 1.17) p-value 0.0222). The statistical significance of both identified cases and recovered return cases on log10 viral RNA copies/L in wastewater indicates the importance of including both types of clinical data in wastewater-based epidemiology (WBE) research. Genetic mutations associated with variants of concern (VOCs) were also monitored. The emergence of the Alpha variant on campus was identified, which contributed to the second wave of COVID-19 cases at UofSC. The study was able to identify sub-community transmission hotspots for targeted intervention in real-time, making WBE cost-effective and creating less of a burden on the general public compared to repeated individual testing methods.
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Project description:Targeted wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been proposed by the United States Centers for Disease Control and Prevention's National Wastewater Surveillance System as a complementary approach to clinical surveillance to detect the presence of Coronavirus Disease 2019 (COVID-19) at high-density facilities and institutions such as university campuses, nursing homes, and correctional facilities. In this study we evaluated the efficacy of targeted wastewater surveillance of SARS-CoV-2 RNA together with individual-level testing for outbreak mitigation on a university campus during Fall 2020 semester. Wastewater samples (n = 117) were collected weekly from manholes or sewer cleanouts that receive wastewater inputs from dormitories, community-use buildings, and a COVID-19 isolation dormitory. Quantitative RT-PCR N1 and N2 assays were used to measure SARS-CoV-2 nucleocapsid genes in wastewater. Due to varying human waste input in different buildings, pepper mild mottle virus (PMMV) RNA was also measured in all samples and used to normalize SARS-CoV-2 N1 and N2 RNA wastewater concentrations. In this study, temporal trends of SARS-CoV-2 in wastewater samples mirrored trends in COVID-19 cases detected on campus. Normalizing SARS-CoV-2 RNA concentrations using human fecal indicator, PMMV enhanced the correlation between N1 and N2 gene abundances in wastewater with COVID-19 cases. N1 and N2 genes were significant predictors of COVID-19 cases in dormitories, and the N2 gene was significantly correlated with the number of detected COVID-19 cases in dormitories. By implementing several public health surveillance programs include targeted wastewater surveillance, individual-level testing, contact tracing, and quarantine/isolation facilities, university health administrators could act decisively during an outbreak on campus, resulting in rapid decline of newly detected COVID-19 cases. Wastewater surveillance of SARS-CoV-2 is a proactive outbreak monitoring tool for university campuses seeking to continue higher education practices in person during the COVID-19 pandemic.
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Project description:This study uses wastewater-based epidemiology (WBE) to rapidly and, through targeted surveillance, track the geographical distribution of SARS-CoV-2 variants of concern (Alpha, Beta and Delta) within 24 wastewater treatment plants (WWTPs) in the Western Cape of South Africa. Information obtained was used to identify the circulating variant of concern (VOC) within a population and retrospectively trace when the predominant variant was introduced. Genotyping analysis of SARS-CoV-2 showed that 50% of wastewater samples harbored signature mutations linked to the Beta variant before the third wave, with the Delta variant absent within the population. Over time, the prevalence of the beta variant decreased steadily. The onset of the third wave resulted in the Delta variant becoming the predominant variant, with a 100% prevalence supporting the theory that the Delta variant was driving the third wave. In silico molecular docking analysis showed that the signature mutations of the Delta variant increased binding to host proteins, suggesting a possible molecular mechanism that increased viral infectivity of the Delta variant.
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