Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance.

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.

Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: A six-month long study in Charlotte, North Carolina.

The global spread of SARS-CoV-2 has continued to be a serious concern after WHO declared the virus to be the causative agent of the coronavirus disease 2019 (COVID-19) a global pandemic. Monitoring of wastewater is a useful tool for assessing community prevalence given that fecal shedding of SARS-CoV-2 occurs in high concentrations by infected individuals, regardless of whether they are asymptomatic or symptomatic. Using tools that are part of wastewater-based epidemiology (WBE) approach, combined with molecular analyses, wastewater monitoring becomes a key piece of information used to assess trends and quantify the scale and dynamics of COVID-19 infection in a specific community, municipality, or area of service. This study investigates a six-month long SARS-CoV-2 RNA quantification in influent wastewater from four municipal wastewater treatment plants (WWTP) serving the Charlotte region of North Carolina (NC) using both RT-qPCR and RT-ddPCR platforms. Influent wastewater was analyzed for the nucleocapsid (N) genes N1 and N2. Both RT-qPCR and RT-ddPCR performed well for detection and quantification of SARS-CoV-2 using the N1 target, while for the N2 target RT-ddPCR was more sensitive. SARS-CoV-2 concentration ranged from 103 to 105 copies/L for all four plants. Both RT-qPCR and RT-ddPCR showed a significant positive correlation between SARS-CoV-2 concentrations and the 7-day rolling average of clinically reported COVID-19 cases when lagging 5 to 12 days (ρ = 0.52-0.92, p < 0.001-0.02). A major finding of this study is that RT-qPCR and RT-ddPCR generated SARS-CoV-2 data that was positively correlated (ρ = 0.569, p < 0.0001) and can be successfully used to monitor SARS-CoV-2 signals across the WWTP of different sizes and metropolitan service functions without significant anomalies.

Assessing sensitivity and reproducibility of RT-ddPCR and RT-qPCR for the quantification of SARS-CoV-2 in wastewater.

Throughout the COVID-19 global pandemic there has been significant interest and investment in using Wastewater-Based Epidemiology (WBE) for surveillance of viral pathogen presence and infections at the community level. There has been a push for widescale implementation of standardized protocols to quantify viral loads in a range of wastewater systems. To address concerns regarding sensitivity, limits of quantification, and large-scale reproducibility, a comparison of two similar workflows using RT-qPCR and RT-ddPCR was conducted. Sixty raw wastewater influent samples were acquired from nine distinct wastewater treatment plants (WWTP's) served by the Hampton Roads Sanitation District (HRSD, Virginia Beach, Virginia) over a 6-month period beginning March 9th, 2020. Common reagents, controls, master mixes and nucleic acid extracts were shared between two individual processing groups based out of HRSD and the UNC Chapel Hill Institute of Marine Sciences (IMS, Morehead City, North Carolina). Samples were analyzed in parallel using One-Step RT-qPCR and One-Step RT-ddPCR with Nucleocapsid Protein 2 (N2) specific primers and probe. Influent SARS-CoV-2 N2 concentrations steadily increased over time spanning a range from non-detectable to 2.13E + 05 copies/L. Systematic dilution of the extracts indicated that inhibitory components in the wastewater matrices did not significantly impede the detection of a positive N2 signal for either workflow. The RT-ddPCR workflow had a greater analytical sensitivity with a lower Limit of Detection (LOD) at 0.066 copies/µl of template compared to RT-qPCR with a calculated LOD of 12.0 copies/µL of template. Interlaboratory comparisons using non-parametric correlation analysis demonstrated that there was a strong, significant, positive correlation between split extracts when employing RT-ddPCR for analysis with a ρ value of 0.86.

Mitochondrial 8-oxoguanine DNA glycosylase mitigates alveolar epithelial cell PINK1 deficiency, mitochondrial DNA damage, apoptosis, and lung fibrosis.

Alveolar epithelial cell (AEC) apoptosis, arising from mitochondrial dysfunction and mitophagy defects, is important in mediating idiopathic pulmonary fibrosis (IPF). Our group established a role for the mitochondrial (mt) DNA base excision repair enzyme, 8-oxoguanine-DNA glycosylase 1 (mtOGG1), in preventing oxidant-induced AEC mtDNA damage and apoptosis and showed that OGG1-deficient mice have increased lung fibrosis. Herein, we determined whether mice overexpressing the mtOGG1 transgene (mtOgg1tg) are protected against lung fibrosis and whether AEC mtOGG1 preservation of mtDNA integrity mitigates phosphatase and tensin homolog-induced putative kinase 1 (PINK1) deficiency and apoptosis. Compared with wild type (WT), mtOgg1tg mice have diminished asbestos- and bleomycin-induced pulmonary fibrosis that was accompanied by reduced lung and AEC mtDNA damage and apoptosis. Asbestos and H2O2 promote the MLE-12 cell PINK1 deficiency, as assessed by reductions in the expression of PINK1 mRNA and mitochondrial protein expression. Compared with WT, Pink1-knockout (Pink1-KO) mice are more susceptible to asbestos-induced lung fibrosis and have increased lung and alveolar type II (AT2) cell mtDNA damage and apoptosis. AT2 cells from Pink1-KO mice and PINK1-silenced (siRNA) MLE-12 cells have increased mtDNA damage that is augmented by oxidative stress. Interestingly, mtOGG1 overexpression attenuates oxidant-induced MLE-12 cell mtDNA damage and apoptosis despite PINK1 silencing. mtDNA damage is increased in the lungs of patients with IPF as compared with controls. Collectively, these findings suggest that mtOGG1 maintenance of AEC mtDNA is crucial for preventing PINK1 deficiency that promotes apoptosis and lung fibrosis. Given the key role of AEC apoptosis in pulmonary fibrosis, strategies aimed at preserving AT2 cell mtDNA integrity may be an innovative target.

Ultraviolet disinfection impacts the microbial community composition and function of treated wastewater effluent and the receiving urban river.

BACKGROUND: In the United States, an estimated 14,748 wastewater treatment plants (WWTPs) provide wastewater collection, treatment, and disposal service to more than 230 million people. The quality of treated wastewater is often assessed by the presence or absence of fecal indicator bacteria. UV disinfection of wastewater is a common final treatment step used by many wastewater treatment plants in order to reduce fecal coliform bacteria and other pathogens; however, its potential impacts on the total effluent bacterial community are seemingly varied. This is especially important given that urban WWTPs typically return treated effluent to coastal and riverine environments and thus are a major source of microorganisms, genes, and chemical compounds to these systems. Following rainfall, stormflow conditions can result in substantial increases to effluent flow into combined systems. METHODS: Here, we conducted a lab-scale UV disinfection on WWTP effluent using UV dosage of 100 mJ/cm2 and monitored the active microbiome in UV-treated effluent and untreated effluent over the course of 48 h post-exposure using 16S rRNA sequencing. In addition, we simulated stormflow conditions with effluent UV-treated and untreated effluent additions to river water and compared the microbial communities to those in baseflow river water. We also tracked the functional profiles of genes involved in tetracycline resistance (tetW) and nitrification (amoA) in these microcosms using RT-qPCR. RESULTS: We showed that while some organisms, such as members of the Bacteroidetes, are inhibited by UV disinfection and overall diversity of the microbial community decreases following treatment, many organisms not only survive, but remain active. These include common WWTP-derived organisms such as Comamonadaceae and Pseudomonas. When combined with river water to mimic stormflow conditions, these organisms can persist in the environment and potentially enhance microbial functions such as nitrification and antibiotic resistance.