Effect of storage conditions on SARS-CoV-2 RNA quantification in wastewater solids.
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ABSTRACT:
SUBMITTER: Simpson A
PROVIDER: S-EPMC8364322 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The COVID-19 pandemic presents many public health challenges including the tracking of infected individuals from local to regional scales. Wastewater surveillance of viral RNA has emerged as a complementary approach to track and monitor the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in a variety of communities of different land use and population size. In the present study, we investigate how five different parameters (pasteurization, storage temperature, storage time, polyethylene glycol (PEG) concentration, and pellet mass) affect the detection of the SARS-CoV-2 N gene and fecal abundance indicator pepper mild mottle virus (PMMoV) gene. Pre-treatment of 24-h composite wastewater samples (n = 14) by pasteurization at 60 °C resulted in a significant reduction of total RNA concentration and copies of the SARS-CoV-2 N gene copies/L (paired Student's t-test, P < 0.05). Comparing the wastewater samples collected from 6 wastewater treatment plants (WWTPs) for a storage period of 7 and 14 days at 4 °C, -20 °C and -80 °C, demonstrated a decrease in SARS-CoV-2 N gene copies/L when samples were stored for 14 days at -20 °C. Polyethylene glycol-NaCl for purification and concentration of viral particles from the wastewater samples demonstrated that a short PEG incubation of 2 h during centrifugation at 4 °C was sufficient for the consistent detection of the SARS-CoV-2 N gene from a 30 mL sample volume. Combined, this paper presents method recommendations for developing a reliable, accurate, sensitive, and reproducible estimation of the SARS-CoV-2 virus in diverse domestic wastewater samples.
| S-EPMC8788100 | biostudies-literature
Project description:Limited information is available on the decay rate of endogenous SARS-CoV-2 and pepper mild mottle virus (PMMoV) RNA in wastewater and primary settled solids, potentially limiting an understanding of how transit or holding times within wastewater infrastructure might impact RNA measurements and their relationship to community COVID-19 infections. In this study, primary settled solids samples were collected from two wastewater treatment plants in the San Francisco Bay Area. Samples were thoroughly mixed, aliquoted into subsamples, and stored at 4, 22, and 37 °C for 10 days. The concentrations of SARS-CoV-2 (N1 and N2 targets) and PMMoV RNA were measured using an RT-ddPCR. Limited decay (<1 log10 reduction) was observed in the detection of viral RNA targets at all temperature conditions, suggesting that SARS-CoV-2 and PMMoV RNA can be highly persistent in solids. First-order decay rate constants ranged from 0.011 to 0.098 day-1 for SARS-CoV-2 RNA and from 0.010 to 0.091 day-1 for PMMoV RNA depending on the temperature conditions. A slower decay was observed for SARS-CoV-2 RNA in primary settled solids compared to previously reported decay in wastewater influent. Further research is needed to understand if solid content and wastewater characteristics might influence the persistence of viral RNA targets.
| S-EPMC8938836 | biostudies-literature
Project description:Despite the widespread adoption of wastewater surveillance, more research is needed to understand the fate and transport of viral genetic markers in wastewater. This information is essential for optimizing monitoring strategies and interpreting wastewater surveillance data. In this study, we examined the solid-liquid partitioning behavior of four viruses in wastewater: SARS-CoV-2, respiratory syncytial virus (RSV), rhinovirus (RV), and F+ coliphage/MS2. We used two approaches: (1) laboratory partitioning experiments using lab-grown viruses and (2) distribution experiments using endogenous viruses in raw wastewater. Partition experiments were conducted at 4 and 22 °C. Wastewater samples were spiked with varying concentrations of each virus, solids and liquids were separated via centrifugation, and viral RNA concentrations were quantified using reverse-transcription-digital droplet PCR (RT-ddPCR). For the distribution experiments, wastewater samples were collected from six wastewater treatment plants and processed without spiking exogenous viruses; viral RNA concentrations were measured in wastewater solids and liquids. In both experiments, RNA concentrations were higher in the solid fraction than the liquid fraction by approximately 3-4 orders of magnitude. Partition coefficients (KF) ranged from 2000-270,000 mL·g-1 across viruses and temperature conditions. Distribution coefficients (Kd) were consistent with results from partitioning experiments. Further research is needed to understand how virus and wastewater characteristics might influence the partitioning of viral genetic markers in wastewater.
| S-EPMC10501194 | biostudies-literature
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.
| S-EPMC8423229 | biostudies-literature
Project description:Since the start of the COVID-19 pandemic, different methods have been used to detect the presence of genetic material of SARS-CoV-2 in wastewater. The use of wastewater for SARS-CoV-2 RNA detection and quantification showed different problems, associated to the complexity of the matrix and the lack of standard methods used to analyze the presence of an enveloped virus, such as coronavirus. Different strategies for the concentration process were selected to carry out the detection and quantification of SARS-CoV-2 RNA in wastewater: (a) aluminum hydroxide adsorption-precipitation, (b) pre-treatment with glycine buffer and precipitation with polyethylene-glycol (PEG) and (c) ultrafiltration (Centricon). Our results showed that the reduction of organic matter, using the pre-treatment with glycine buffer before the concentration with Centricon or aluminum hydroxide adsorption-precipitation, improved the recovery percentage of the control virus, Mengovirus (MgV) (8.37% ± 5.88 n = 43; 6.97% ± 6.51 n = 20, respectively), and the detection of SARS-CoV-2 in comparison with the same methodology without a pre-treatment. For the concentration with Centricon, the use of 100 mL of wastewater, instead of 200 mL, increased the MgV recovery, and allowed a positive detection of SARS-CoV-2 with N1 and N2 targets. The quantity of SARS-CoV-2 RNA detected in wastewater did not show a direct correlation with the number of confirmed cases, but the study of its upwards or downwards trend over time enabled the detection of an increase of epidemiological data produced in September 2020, January 2021 and April 2021.
| S-EPMC9063616 | biostudies-literature
Project description:In the absence of an effective vaccine to prevent COVID-19 it is important to be able to track community infections to inform public health interventions aimed at reducing the spread and therefore reduce pressures on health-care, improve health outcomes and reduce economic uncertainty. Wastewater surveillance has rapidly emerged as a potential tool to effectively monitor community infections through measuring trends of RNA signal in wastewater systems. In this study SARS-CoV-2 viral RNA N1 and N2 gene regions are quantified in solids collected from influent post grit solids (PGS) and primary clarified sludge (PCS) in two water resource recovery facilities (WRRF) serving Canada's national capital region, i.e., the City of Ottawa, ON (pop. ≈ 1.1M) and the City of Gatineau, QC (pop. ≈ 280K). PCS samples show signal inhibition using RT-ddPCR compared to RT-qPCR, with PGS samples showing similar quantifiable concentrations of RNA using both assays. RT-qPCR shows higher frequency of detection of N1 and N2 gene regions in PCS (92.7, 90.6%, n = 6) as compared to PGS samples (79.2, 82.3%, n = 5). Sampling of PCS may therefore be an effective approach for SARS-CoV-2 viral quantification, especially during periods of declining and low COVID-19 incidence in the community. The pepper mild mottle virus (PMMoV) is determined to have a less variable RNA signal in PCS over a three month period for two WRRFs, regardless of environmental conditions, compared to Bacteroides 16S rRNA or human 18S rRNA, making PMMoV a potentially useful biomarker for normalization of SARS-CoV-2 signal. PMMoV-normalized PCS RNA signal from WRRFs of two cities correlated with the regional public health epidemiological metrics, identifying PCS normalized to a fecal indicator (PMMoV) as a potentially effective tool for monitoring trends during decreasing and low-incidence of infection of SARS-Cov-2 in communities.
| S-EPMC7583624 | biostudies-literature
Project description: Not available
| S-EPMC8018904 | biostudies-literature
Project description:Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in wastewater can potentially provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2 RNA in wastewater, culminating in recommended strategies that can be implemented to identify and mitigate some of these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, PCR inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.
| S-EPMC8386095 | biostudies-literature
Project description:The COVID-19 pandemic and the detection of SARS-CoV-2 RNA in sewage has expanded global interest in wastewater surveillance. However, many underserved communities throughout the world lack improved sanitation and use informal combined sanitary and storm sewer systems. Sewage is transported via open channels, ditches, and rivers, where it mixes with surface water and/or stormwater. There is a need to develop better methods for the surveillance of pathogens such as SARS-CoV-2 RNA in this context. We developed a simplified surveillance system and monitored flow rates and concentrations of SARS-CoV-2 RNA in the Tijuana River at two locations downstream of the United States-Mexico border in California, United States. SARS-CoV-2 RNA was detected in the upstream location on six out of eight occasions, two of which were at concentrations as high as those reported in untreated wastewater from California sanitary sewer systems. The virus was not detected in any of the eight samples collected at the downstream (estuarine) sampling location, despite the consistent detection of PMMoV RNA. Synchrony was observed between the number of cases reported in Tijuana and the SARS-CoV-2 RNA concentrations measured with the CDC N1 assay when the latter were normalized by the reported flow rates in the river.
| S-EPMC9063987 | biostudies-literature
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater settled solids correlate well with coronavirus disease 2019 (COVID-19) incidence rates (IRs). Here, we develop distributed lag models to estimate IRs using concentrations of SARS-CoV-2 RNA from wastewater solids and investigate the impact of sampling frequency on model performance. SARS-CoV-2 N gene and pepper mild mottle virus (PMMoV) RNA concentrations were measured daily at four wastewater treatment plants in California. Artificially reduced data sets were produced for each plant with sampling frequencies of once every 2, 3, 4, and 7 days. Sewershed-specific models that related daily N/PMMoV to IR were fit for each sampling frequency with data from mid-November 2020 through mid-July 2021, which included the period of time during which Delta emerged. Models were used to predict IRs during a subsequent out-of-sample time period. When sampling occurred at least once every 4 days, the in- and out-of-sample root-mean-square error changed by <7 cases/100 000 compared to daily sampling across sewersheds. This work illustrates that real-time, daily predictions of IR are possible with small errors, despite changes in circulating variants, when sampling frequency is once every 4 days or more. However, reduced sampling frequency may not serve other important wastewater surveillance use cases.
| S-EPMC9092194 | biostudies-literature