Detection of SARS-CoV-2 RNA in Medical Wastewater in Wuhan During the COVID-19 Outbreak.
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ABSTRACT:
SUBMITTER: Zhou JB
PROVIDER: S-EPMC8090523 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater samples has been documented in several countries. Wastewater-based epidemiology (WBE) is potentially effective for early warning of a COVID-19 outbreak. In this study, presence of SARS-CoV-2 RNA in wastewater samples was investigated and was compared with the number of the confirmed COVID-19 cases in the study area during COVID-19 outbreak in Japan. In total, 45 influent wastewater samples were collected from five wastewater treatment plants in Ishikawa and Toyama prefectures in Japan. During the study period, the numbers of confirmed COVID-19 cases in these prefectures increased from 0.3 and 0 to >20 per 100,000 people. SARS-CoV-2 ribonucleic acid (RNA) in the samples was detected using several PCR-based assays. Of the 45 samples, 21 were positive for SARS-CoV-2 according to at least one of the three quantitative RT-PCR assays. The detection frequency increased when the number of total confirmed SARS-CoV-2 cases in 100,000 people exceeded 10 in each prefecture; however, SARS-CoV-2 could also be detected at a low frequency even when the number was below 1.0. SARS-CoV-2 in wastewater could be detected in the early stage of the epidemic, even if the number of confirmed cases potentially underestimates the actual numbers of cases. This suggests that WBE approach can potentially act as an early warning of COVID-19 outbreaks in Japan.
| S-EPMC7654358 | biostudies-literature
Project description:Wastewater treatment plants (WWTPs) are the final stage of the anthropogenic water cycle where a wide range of chemical and biological markers of human activity can be found. In COVID-19 disease contexts, wastewater surveillance has been used to infer community trends based on viral abundance and SARS-CoV-2 RNA variant composition, which has served to anticipate and establish appropriate protocols to prevent potential viral outbreaks. Numerous studies worldwide have provided reliable and robust tools to detect and quantify SARS-CoV-2 RNA in wastewater, although due to the high dilution and degradation rate of the viral RNA in such samples, the detection limit of the pathogen has been a bottleneck for the proposed protocols so far. The current work provides a comprehensive and systematic study of the different parameters that may affect the detection of SARS-CoV-2 RNA in wastewater and hinder its quantification. The results obtained using synthetic viral RNA as a template allow us to consider that 10 genome copies per µL is the minimum RNA concentration that provides reliable and consistent values for the quantification of SARS-CoV-2 RNA. RT-qPCR analysis of wastewater samples collected at the WWTP in Salamanca (western Spain) and at six pumping stations in the city showed that below this threshold, positive results must be confirmed by sequencing to identify the specific viral sequence. This allowed us to find correlations between the SARS-CoV-2 RNA levels found in wastewater and the COVID-19 clinical data reported by health authorities. The close match between environmental and clinical data from the Salamanca case study has been confirmed by similar experimental approaches in four other cities in the same region. The present methodological approach reinforces the usefulness of wastewater-based epidemiology (WBE) studies in the face of future pandemic outbreaks.
| S-EPMC11311535 | biostudies-literature
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.
| S-EPMC8163699 | biostudies-literature
Project description:Raw municipal wastewater from five wastewater treatment plants representing the vast majority of the Qatar population was sampled between the third week of June 2020 and the end of August 2020, during the period of declining cases after the peak of the first wave of infection in May 2020. The N1 region of the SARS-CoV-2 genome was used to quantify the viral load in the wastewater using RT-qPCR. The trend in Ct values in the wastewater samples mirrored the number of new daily positive cases officially reported for the country, confirmed by RT-qPCR testing of naso-pharyngeal swabs. SARS-CoV-2 RNA was detected in 100% of the influent wastewater samples (7889 ± 1421 copy/L - 542,056 ± 25,775 copy/L, based on the N1 assay). A mathematical model for wastewater-based epidemiology was developed and used to estimate the number of people in the population infected with COVID-19 from the N1 Ct values in the wastewater samples. The estimated number of infected population on any given day using the wastewater-based epidemiology approach declined from 542,313 ± 51,159 to 31,181 ± 3081 over the course of the sampling period, which was significantly higher than the officially reported numbers. However, seroprevalence data from Qatar indicates that diagnosed infections represented only about 10% of actual cases. The model estimates were lower than the corrected numbers based on application of a static diagnosis ratio of 10% to the RT-qPCR identified cases, which is assumed to be due to the difficulty in quantifying RNA losses as a model term. However, these results indicate that the presented WBE modeling approach allows for a realistic assessment of incidence trend in a given population, with a more reliable estimation of the number of infected people at any given point in time than can be achieved using human biomonitoring alone.
| S-EPMC7870436 | biostudies-literature
Project description:ACE2 on epithelial cells is the SARS-CoV-2 entry receptor. Single-cell RNA-sequencing data derived from two COVID-19 cohorts revealed that MAP4K3/GLK-positive epithelial cells were increased in patients. SARS-CoV-2-induced GLK overexpression in epithelial cells correlated with COVID-19 severity and vesicle secretion. GLK overexpression induced the epithelial cell-derived exosomes containing ACE2; the GLK-induced exosomes transported ACE2 proteins to recipient cells, facilitating pseudovirus infection. Consistently, ACE2 proteins were increased in the serum exosomes from another COVID-19 cohort. Remarkably, SARS-CoV-2 spike protein stimulated GLK, and GLK stabilized ACE2 in epithelial cells. Mechanistically, GLK phosphorylated ACE2 at two serine residues (Ser776, Ser783), leading to dissociation of ACE2 from its E3 ligase UBR4. Reduction of UBR4-induced Lys48-linked ubiquitination at three lysine residues (Lys26, Lys112, Lys114) of ACE2 prevented its degradation. Furthermore, SARS-CoV-2 pseudovirus or live virus infection in humanized ACE2 mice induced GLK and ACE2 protein levels, as well as ACE2-containing exosomes. Collectively, ACE2 stabilization by SARS-CoV-2-induced MAP4K3/GLK may contribute to the pathogenesis of COVID-19.
| S-SCDT-EMM-2022-15904 | biostudies-other
Project description:Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.
| S-EPMC9639408 | biostudies-literature
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 200,000 reported COVID-19 cases in Spain resulting in more than 20,800 deaths as of April 21, 2020. Faecal shedding of SARS-CoV-2 RNA from COVID-19 patients has extensively been reported. Therefore, we investigated the occurrence of SARS-CoV-2 RNA in six wastewater treatments plants (WWTPs) serving the major municipalities within the Region of Murcia (Spain), the area with the lowest COVID-19 prevalence within Iberian Peninsula. Firstly, an aluminum hydroxide adsorption-precipitation concentration method was validated using a porcine coronavirus (Porcine Epidemic Diarrhea Virus, PEDV) and mengovirus (MgV). The procedure resulted in average recoveries of 10 ± 3.5% and 10 ± 2.1% in influent water (n = 2) and 3.3 ± 1.6% and 6.2 ± 1.0% in effluent water (n = 2) samples for PEDV and MgV, respectively. Then, the method was used to monitor the occurrence of SARS-CoV-2 from March 12 to April 14, 2020 in influent, secondary and tertiary effluent water samples. By using the real-time RT-PCR (RT-qPCR) Diagnostic Panel validated by US CDC that targets three regions of the virus nucleocapsid (N) gene, we estimated quantification of SARS-CoV-2 RNA titers in untreated wastewater samples of 5.4 ± 0.2 log10 genomic copies/L on average. Two secondary water samples resulted positive (2 out of 18) and all tertiary water samples tested as negative (0 out 12). This environmental surveillance data were compared to declared COVID-19 cases at municipality level, revealing that members of the community were shedding SARS-CoV-2 RNA in their stool even before the first cases were reported by local or national authorities in many of the cities where wastewaters have been sampled. The detection of SARS-CoV-2 in wastewater in early stages of the spread of COVID-19 highlights the relevance of this strategy as an early indicator of the infection within a specific population. At this point, this environmental surveillance could be implemented by municipalities right away as a tool, designed to help authorities to coordinate the exit strategy to gradually lift its coronavirus lockdown.
| S-EPMC7229723 | biostudies-literature
Project description: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.
| S-EPMC9824953 | biostudies-literature
Project description:This study monitored the presence of SARS-Cov-2 RNA on environmental surfaces in hospital wards housing patients with mild, severe, and convalescent Coronavirus Disease 2019 (COVID-19), respectively. From 29 October to 4 December 2021, a total of 787 surface samples were randomly collected from a General Ward, Intensive Care Unit, and Convalescent Ward at a designated hospital for COVID-19 patients in China. All of the samples were used for SARS-Cov-2 detection. Descriptive statistics were generated and differences in the positivity rates between the wards were analyzed using Fisher's exact tests, Yates chi-squared tests, and Pearson's chi-squared tests. During the study period, 787 surface samples were collected, among which, 46 were positive for SARS-Cov-2 RNA (5.8%). The positivity rate of the contaminated area in the Intensive Care Unit was higher than that of the General Ward (23.5% vs. 10.4%, P<0.05). The positivity rate of the semi-contaminated area in the Intensive Care Unit (4.5%) was higher than that of the General Ward (1.5%), but this difference was not statistically significant (P>0.05). In the clean area, only one sample was positive in the Intensive Care Unit (0.5%). None of the samples were positive in the Convalescent Ward. These findings reveal that the SARS-Cov-2 RNA environmental pollution in the Intensive Care Unit was more serious than that in the General Ward, while the pollution in the Convalescent Ward was the lowest. Strict disinfection measures, personal protection, and hand hygiene are necessary to limit the spread of SARS-Cov-2.
| S-EPMC10212077 | biostudies-literature
Project description:The applicability of wastewater-based epidemiology (WBE) has been extensively studied throughout the world with remarkable findings. This study reports the presence and reduction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at two wastewater treatment plants (WWTPs) of Nepal, along with river water, hospital wastewater (HWW), and wastewater from sewer lines collected between July 2020 and February 2021. SARS-CoV-2 RNA was detected in 50%, 54%, 100%, and 100% of water samples from WWTPs, river hospitals, and sewer lines, respectively, by at least one of four quantitative PCR assays tested (CDC-N1, CDC-N2, NIID_2019-nCOV_N, and N_Sarbeco). The CDC-N2 assay detected SARS-CoV-2 RNA in the highest number of raw influent samples of both WWTPs. The highest concentration was observed for an influent sample of WWTP A (5.5 ± 1.0 log10 genome copies/L) by the N_Sarbeco assay. SARS-CoV-2 was detected in 47% (16/34) of the total treated effluents of WWTPs, indicating that biological treatments installed at the tested WWTPs are not enough to eliminate SARS-CoV-2 RNA. One influent sample was positive for N501Y mutation using the mutation-specific qPCR, highlighting a need for further typing of water samples to detect Variants of Concern. Furthermore, crAssphage-normalized SARS-CoV-2 RNA concentrations in raw wastewater did not show any significant association with the number of new coronavirus disease 2019 (COVID-19) cases in the whole district where the WWTPs were located, suggesting a need for further studies focusing on suitability of viral as well as biochemical markers as a population normalizing factor. Detection of SARS-CoV-2 RNA before, after, and during the peaking in number of COVID-19 cases suggests that WBE is a useful tool for COVID-19 case estimation in developing countries.
| S-EPMC8832950 | biostudies-literature