Comparative Analysis of RNA-Extraction Approaches and Associated Influences on RT-qPCR of the SARS-CoV-2 RNA in a University Residence Hall and Quarantine Location

Improved SARS-CoV-2 RNA recovery in wastewater matrices using a CTAB-based extraction method

Wastewater-based epidemiology has allowed tracking the magnitude and distribution of SARS-CoV-2 in communities, allowing public health officials to prepare for impending outbreaks. While many factors influence recovery of SARS-CoV-2 from wastewater, proper extraction, concentration, and purification of RNA are key steps to ensure accurate detection of viral particles. The aim of this study was to compare the efficiency of four commonly used RNA extraction methods for detection of the SARS-CoV-2 RNA genome in sewage samples artificially inoculated with the virus, in order to identify a protocol that improves viral recovery. These methods included CTAB-based, TRIzol-based, and guanidinium thiocyanate (GTC)-based extraction procedures coupled with silica spin column-based purification, and an automated extraction/purification protocol using paramagnetic particles. Following RNA extraction, virus recovery rates were compared using RT-qPCR-based detection. The CTAB-based approach yielded the highest recovery rates and was the only method to consistently demonstrate stable virus recovery percentages regardless of the specific physicochemical characteristics of the samples tested. The TRIzol method proved to be the second most effective, yielding significantly higher recovery rates compared to both the GTC-based and the automated extraction methods. These results suggest that the CTAB-based approach could be a useful tool for the recovery of viral RNA from complex wastewater matrices.

Influences of 23 different equations used to calculate gene copies of SARS-CoV-2 during wastewater-based epidemiology

Following the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, the use of wastewater-based surveillance (WBS) has increased dramatically along with associated infrastructure globally. However, due to the global nature of its application, and various workflow adaptations (e.g., sample collection, water concentration, RNA extraction kits), numerous methods for back-calculation of gene copies per volume (gc/L) of sewage have also emerged. Many studies have considered the comparability of processing methods (e.g., water concentration, RNA extraction); however, for equations used to calculate gene copies in a wastewater sample and subsequent influences on monitoring viral trends in a community and its association with epidemiological data, less is known. Due to limited information on how many formulas exist for the calculation of SARS-CoV-2 gene copies in wastewater, we initially attempted to quantify how many equations existed in the referred literature. We identified 23 unique equations, which were subsequently applied to an existing wastewater dataset. We observed a range of gene copies based on use of different equations, along with variability of AUC curve values, and results from correlation and regression analyses. Though a number of individual laboratories appear to have independently converged on a similar formula for back-calculation of viral load in wastewater, and share similar relationships with epidemiological data, differential influences of various equations were observed for variation in PCR volumes, RNA extraction volumes, or PCR assay parameters. Such observations highlight challenges when performing comparisons among WBS studies when numerous methodologies and back-calculation methods exist. To facilitate reproducibility among studies, the different gc/L equations were packaged as an R Shiny app, which provides end users the ability to investigate variability within their datasets and support comparisons among studies.

Evaluating various composite sampling modes for detecting pathogenic SARS-CoV-2 virus in raw sewage

Inadequate sampling approaches to wastewater analyses can introduce biases, leading to inaccurate results such as false negatives and significant over- or underestimation of average daily viral concentrations, due to the sporadic nature of viral input. To address this challenge, we conducted a field trial within the University of Tennessee residence halls, employing different composite sampling modes that encompassed different time intervals (1 h, 2 h, 4 h, 6 h, and 24 h) across various time windows (morning, afternoon, evening, and late-night). Our primary objective was to identify the optimal approach for generating representative composite samples of SARS-CoV-2 from raw wastewater. Utilizing reverse transcription-quantitative polymerase chain reaction, we quantified the levels of SARS-CoV-2 RNA and pepper mild mottle virus (PMMoV) RNA in raw sewage. Our findings consistently demonstrated that PMMoV RNA, an indicator virus of human fecal contamination in water environment, exhibited higher abundance and lower variability compared to pathogenic SARS-CoV-2 RNA. Significantly, both SARS-CoV-2 and PMMoV RNA exhibited greater variability in 1 h individual composite samples throughout the entire sampling period, contrasting with the stability observed in other time-based composite samples. Through a comprehensive analysis of various composite sampling modes using the Quade Nonparametric ANCOVA test with date, PMMoV concentration and site as covariates, we concluded that employing a composite sampler during a focused 6 h morning window for pathogenic SARS-CoV-2 RNA is a pragmatic and cost-effective strategy for achieving representative composite samples within a single day in wastewater-based epidemiology applications. This method has the potential to significantly enhance the accuracy and reliability of data collected at the community level, thereby contributing to more informed public health decision-making during a pandemic.

Influence of storage conditions and multiple freeze-thaw cycles on N1 SARS-CoV-2, PMMoV, and BCoV signal

Wastewater-based epidemiology/wastewater-based surveillance (WBE/WBS) continues to serve as an effective means of monitoring various diseases, including COVID-19 and the emergence of SARS-CoV-2 variants, at the population level. As the use of WBE expands, storage conditions of wastewater samples will play a critical role in ensuring the accuracy and reproducibility of results. In this study, the impacts of water concentration buffer (WCB), storage temperature, and freeze-thaw cycles on the detection of SARS-CoV-2 and other WBE-related gene targets were examined. Freeze-thawing of concentrated samples did not significantly affect (p > 0.05) crossing/cycle threshold (Ct) value for any of the gene targets studied (SARS-CoV-2 N1, PMMoV, and BCoV). However, use of WCB during concentration resulted in a significant (p < 0.05) decrease in Ct for all targets, and storage at -80 °C (in contrast to -20 °C) appeared preferable for wastewater storage signal stability based on decreased Ct values, although this was only significantly different (p < 0.05) for the BCoV target. Interestingly, when Ct values were converted to gene copies per influent sample, no significant differences (p > 0.05) were observed in any of the targets examined. Stability of RNA targets in concentrated wastewater against freeze-thaw degradation supports archiving of concentrated samples for use in retrospective examination of COVID-19 trends and tracing SARS-CoV-2 variants and potentially other viruses, and provides a starting point for establishing a consistent procedure for specimen collection and storage for the WBE/WBS community.

Recent progress on wastewater-based epidemiology for COVID-19 surveillance: A systematic review of analytical procedures and epidemiological modeling

On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19), whose causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pandemic. This virus is predominantly transmitted via respiratory droplets and shed via sputum, saliva, urine, and stool. Wastewater-based epidemiology (WBE) has been able to monitor the circulation of viral pathogens in the population. This tool demands both in-lab and computational work to be meaningful for, among other purposes, the prediction of outbreaks. In this context, we present a systematic review that organizes and discusses laboratory procedures for SARS-CoV-2 RNA quantification from a wastewater matrix, along with modeling techniques applied to the development of WBE for COVID-19 surveillance. The goal of this review is to present the current panorama of WBE operational aspects as well as to identify current challenges related to it. Our review was conducted in a reproducible manner by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. We identified a lack of standardization in wastewater analytical procedures. Regardless, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach was the most reported technique employed to detect and quantify viral RNA in wastewater samples. As a more convenient sample matrix, we suggest the solid portion of wastewater to be considered in future investigations due to its higher viral load compared to the liquid fraction. Regarding the epidemiological modeling, the data-driven approach was consistently used for the prediction of variables associated with outbreaks. Future efforts should also be directed toward the development of rapid, more economical, portable, and accurate detection devices.

Evaluation of low-cost SARS-CoV-2 RNA purification methods for viral quantification by RT-qPCR and next-generation sequencing analysis: Implications for wider wastewater-based epidemiology adoption

Based Epidemiology (WBE) consists of quantifying biomarkers in sewerage systems to derive real-time information on the health and/or lifestyle of the contributing population. WBE usefulness was vastly demonstrated in the context of the COVID-19 pandemic. Many methods for SARS-CoV-2 RNA determination in wastewater were devised, which vary in cost, infrastructure requirements and sensitivity. For most developing countries, implementing WBE for viral outbreaks, such as that of SARS-CoV-2, proved challenging due to budget, reagent availability and infrastructure constraints. In this study, we assessed low-cost methods for SARS-CoV-2 RNA quantification by RT-qPCR, and performed variant identification by NGS in wastewater samples. Results showed that the effect of adjusting pH to 4 and/or adding MgCl2 (25 mM) was negligible when using the adsorption-elution method, as well as basal physicochemical parameters in the sample. In addition, results supported the standardized use of linear rather than plasmid DNA for a more accurate viral RT-qPCR estimation. The modified TRIzol-based purification method in this study yielded comparable RT-qPCR estimation to a column-based approach, but provided better NGS results, suggesting that column-based purification for viral analysis should be revised. Overall, this work provides evaluation of a robust, sensitive and cost-effective method for SARS-CoV-2 RNA analysis that could be implemented for other viruses, for a wider WEB adoption.

Monitoring COVID-19 spread in selected Prague's schools based on the presence of SARS-CoV-2 RNA in wastewater

The COVID-19 pandemic has demanded a broad range of techniques to better monitor its extent. Owing to its consistency, non-invasiveness, and cost effectiveness, wastewater-based epidemiology has emerged as a relevant approach to monitor the pandemic's course. In this work, we analyzed the extent of the COVID-19 pandemic in five primary schools in Prague, the Czech Republic, and how different preventive measures impact the presence of SARS-CoV-2 RNA copy numbers in wastewaters. Copy numbers were measured by reverse transcription-multiplex quantitative real-time PCR. These copy numbers were compared to the number of infected individuals in each school identified through regular clinical tests. Each school had a different monitoring regime and subsequent application of preventive measures to thwart the spread of COVID-19. The schools that constantly identified and swiftly quarantined infected individuals exhibited persistently low amounts of SARS-CoV-2 RNA copies in their wastewaters. In one school, a consistent monitoring of infected individuals, coupled with a delayed action to quarantine, allowed for the estimation of a linear model to predict the number of infected individuals based on the presence of SARS-CoV-2 RNA in the wastewater. The results show the importance of case detection and quarantining to stop the spread of the pandemic and its impact on the presence of SARS-CoV-2 RNA in wastewaters. This work also shows that wastewater-based epidemiological models can be reliably used even in small water catchments, but difficulties arise to fit models due to the nonconstant input of viral particles into the wastewater systems.

Wastewater monitoring of SARS-CoV-2 RNA at K-12 schools: comparison to pooled clinical testing data

Background

Wastewater measurements of SARS-CoV-2 RNA have been extensively used to supplement clinical data on COVID-19. Most examples in the literature that describe wastewater monitoring for SARS-CoV-2 RNA use samples from wastewater treatment plants and individual buildings that serve as the primary residence of community members. However, wastewater surveillance can be an attractive supplement to clinical testing in K-12 schools where individuals only spend a portion of their time but interact with others in close proximity, increasing risk of potential transmission of disease.

Methods

Wastewater samples were collected from two K-12 schools in California and divided into solid and liquid fractions to be processed for detection of SARS-CoV-2. The resulting detection rate in each wastewater fraction was compared to each other and the detection rate in pooled clinical specimens.

Results

Most wastewater samples were positive for SARS-CoV-2 RNA when clinical testing was positive (75% for solid samples and 100% for liquid samples). Wastewater samples continued to test positive for SARS-CoV-2 RNA when clinical testing was negative or in absence of clinical testing (83% for both solid and liquid samples), indicating presence of infected individuals in the schools. Wastewater solids had a higher concentration of SARS-CoV-2 than wastewater liquids on an equivalent mass basis by three orders of magnitude.

Quantitative Reverse Transcription PCR Surveillance of SARS-CoV-2 Variants of Concern in Wastewater of Two Counties in Texas, United States

After its emergence in late November/December 2019, the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) rapidly spread globally. Recognizing that this virus is shed in feces of individuals and that viral RNA is detectable in wastewater, testing for SARS-CoV-2 in sewage collections systems has allowed for the monitoring of a community's viral burden. Over a 9 month period, the influents of two regional wastewater treatment facilities were concurrently examined for wild-type SARS-CoV-2 along with variants B.1.1.7 and B.1.617.2 incorporated as they emerged. Epidemiological data including new confirmed COVID-19 cases and associated hospitalizations and fatalities were tabulated within each location. RNA from SARS-CoV-2 was detectable in 100% of the wastewater samples, while variant detection was more variable. Quantitative reverse transcription PCR (RT-qPCR) results align with clinical trends for COVID-19 cases, and increases in COVID-19 cases were positively related with increases in SARS-CoV-2 RNA load in wastewater, although the strength of this relationship was location specific. Our observations demonstrate that clinical and wastewater surveillance of SARS-CoV-2 wild type and constantly emerging variants of concern can be combined using RT-qPCR to characterize population infection dynamics. This may provide an early warning for at-risk communities and increases in COVID-19 related hospitalizations.