Identification of environmental and methodological factors driving variability of Pepper Mild Mottle Virus (PMMoV) across three wastewater treatment plants in the City of Toronto.

PMMoV has been widely used to normalize the concentration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, influenza, and respiratory syncytial virus (RSV) to account for variations in the fecal content of wastewater. PMMoV is also used as an internal RNA recovery control for wastewater-based epidemiology (WBE) tests. While potentially useful for the interpretation of WBE data, previous studies have suggested that PMMoV concentration can be affected by various physico-chemical characteristics of wastewater. There is also the possibility that laboratory methods, particularly the variability in centrifugation steps to remove supernatant from pellets can cause PMMoV variability. The goal of this study is to improve our understanding of the main drivers of PMMoV variability by assessing the relationship between PMMoV concentration, the physico-chemical characteristics of wastewater, and the methodological approach for concentrating wastewater samples. We analyzed 24-hour composite wastewater samples collected from the influent stream of three wastewater treatment plants (WWTPs) located in the City of Toronto, Ontario, Canada. Samples were collected 3 to 5 times per week starting from the beginning of March 2021 to mid-July 2023. The influent flow rate was used to partition the data into wet and dry weather conditions. Physico-chemical characteristics (e.g., total suspended solids (TSS), biological oxygen demand (BOD), alkalinity, electrical conductivity (EC), and ammonia (NH3)) of the raw wastewater were measured, and PMMoV was quantified. Spatial and temporal variability of PMMoV was observed throughout the study period. PMMoV concentration was significantly higher during dry weather conditions. Multiple linear regression analysis demonstrates that the number and type of physico-chemical parameters that drive PMMoV variability are site-specific, but overall BOD and alkalinity were the most important predictors. Differences in PMMoV concentration for a single WWTP between two different laboratory methods, along with a weak correlation between pellet mass and TSS using one method may indicate that differences in sample concentration and subjective subsampling bias could alter viral recovery and introduce variability to the data.

Underestimation of SARS-CoV-2 in wastewater due to single or double mutations in the N1 qPCR probe binding region.

Wastewater surveillance using RT-qPCR has now been widely adopted to track circulating levels of SARS-CoV-2 virus in many sewersheds. The CDC qPCR assays targeting two regions (N1 and N2) within the N gene are commonly used, but a discrepancy between the two biomarkers has been noticed by independent studies using these methods since late 2021. The reason is presumed to be due to mutations in regions targeted by the N1 qPCR probe. In this study, we systematically investigated and unequivocally confirmed that the underlying reason for this discrepancy was mutations in the N1 probe target, and that a single mutation could cause a significant drop in signal. We first confirmed the proportion of related mutations in wastewater samples (Jan 2021-Dec 2022) using nested PCR and LC-MS. Based on relative proportions of N1 alleles, we separated the wastewater data into four time periods corresponding to different variant waves: Period I (Alpha and Delta waves with 0 mutation), Period II (BA.1/BA.2 waves with a single mutation found in all Omicron strains), Period III (BA.5.2* wave with two mutations), and Period IV (BQ.1* wave with two mutations). Significantly lower N1 copies relative to N2 copies in samples from Periods II-IV compared to those from Period I was observed in wastewater. To further pinpoint the extent to which each mutation impacted N1 quantification, we compared the qPCR response among different synthetic oligomers with corresponding mutations. This study highlighted the impact of even just one or two mutations on qPCR-based wastewater surveillance of SARS-CoV-2.

Microbial community dynamics of a sequentially fed anaerobic digester treating solid organic waste.

A 50-kg scale, high solids anaerobic digester (AD) comprising six sequentially fed leach beds with a leachate recirculation system was operated at 37°C for 88 weeks. The solid feedstock contained a constant fibre fraction (a mix of cardboard, boxboard, newsprint, and fine paper) and varying proportions of food waste. Previously, we reported on the stable operation of this digestion system, where significantly enhanced methane production from the fibre fraction was observed as the proportion of food waste increased. The objective of this study was to identify relationships between process parameters and the microbial community. Increasing food waste led to a large increase in the absolute microbial abundance in the circulating leachate. While 16S rRNA amplicons for Clostridium butyricum were most abundant and correlated with the amount of FW in the system and with the overall methane yield, it was more cryptic Candidatus Roizmanbacteria and Spirochaetaceae that correlated specifically with enhanced methane from the fiber fraction. A faulty batch of bulking agent led to hydraulic channeling, which was reflected in the leachate microbial profiles matching that of the incoming food waste. The system performance and microbial community re-established rapidly after reverting to better bulking agent, illustrating the robustness of the system.

Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities.

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.

A high-throughput and cost-effective microplate reader method for measuring persulfates (peroxydisulfate and peroxymonosulfate).

Frequent use of persulfates as oxidants, for in situ chemical oxidation and advanced oxidation processes, warrants the need for developing a fast and efficient method for measuring persulfate concentrations in aqueous samples in the lab and on site. Here, we propose a modified method, based on Liang et al.'s (2008) spectrophotometric method, for measuring both peroxydisulfate (PDS) and peroxymonosulfate (PMS) in the aqueous samples. Our method involves a deep 96-well plate, multi-channel pipettes, a small orbital shaker, and a microplate reader; allowing the preparation and analysis of up to 96 samples in one run. Our proposed method shortens the time by 10 folds, consumes only ∼2% of the original reagents, and generates only ∼2% of the liquid waste compared to the Liang et al.'s method, thus, making our method high-throughput, time-efficient, and cost-effective with reduced environmental impact. The presented microplate reader method is validated in terms of linearity, LOD, LOQ, accuracy, precision, robustness, and selectivity. All the parameters satisfied the acceptance criteria, according to ICH guidelines. The linearity of calibration curves was evaluated by performing the F-test. In general, our method has linear ranges from 20 to 42,000 and 5 to 40,960 µM for PDS and PMS, respectively. Accuracy (% recovery) results suggested that the LOD and LOQ based on the standard deviation of y-intercepts of the regression lines were the most reliable. The LOD/LOQ values for PDS and PMS were 14.7/44.1 and 4.6/14.4 µM, respectively. The proposed method was also modified to work with a standard cuvette spectrophotometer and was validated. A comparison with the UHPLC analysis of PDS showed that our microplate reader method performed equivalently or even outperformed the UHPLC method, in the presence of common groundwater constituents and organic contaminants.

Early Warning Measurement of SARS-CoV-2 Variants of Concern in Wastewaters by Mass Spectrometry.

Wastewater surveillance has rapidly emerged as an early warning tool to track COVID-19. However, the early warning measurement of new SARS-CoV-2 variants of concern (VOCs) in wastewaters remains a major challenge. We herein report a rapid analytical strategy for quantitative measurement of VOCs, which couples nested polymerase chain reaction and liquid chromatography-mass spectrometry (nPCR-LC-MS). This method showed a greater selectivity than the current allele-specific quantitative PCR (AS-qPCR) for tracking new VOC and allowed the detection of multiple signature mutations in a single measurement. By measuring the Omicron variant in wastewaters across nine Ontario wastewater treatment plants serving over a three million population, the nPCR-LC-MS method demonstrated a better quantification accuracy than next-generation sequencing (NGS), particularly at the early stage of community spreading of Omicron. This work addresses a major challenge for current SARS-CoV-2 wastewater surveillance by rapidly and accurately measuring VOCs in wastewaters for early warning.

Microbial Communities Associated with Sustained Anaerobic Reductive Dechlorination of α-, ß-, γ-, and δ-Hexachlorocyclohexane Isomers to Monochlorobenzene and Benzene.

Intensive historical and worldwide use of pesticide formulations containing hexachlorocyclohexane (HCH) has led to widespread contamination. We derived four anaerobic enrichment cultures from HCH-contaminated soil capable of sustainably dechlorinating each of α-, ß-, γ-, and δ-HCH isomers stoichiometrically to benzene and monochlorobenzene (MCB). For each isomer, the dechlorination rates, inferred from production rates of the dechlorinated products, MCB and benzene, increased progressively from <3 to ∼12 µM/day over 2 years. The molar ratio of benzene to MCB produced was a function of the substrate isomer and ranged from ß (0.77 ± 0.15), α (0.55 ± 0.09), γ (0.13 ± 0.02), to δ (0.06 ± 0.02) in accordance with pathway predictions based on prevalence of antiperiplanar geometry. Data from 16S rRNA gene amplicon sequencing and quantitative PCR revealed significant increases in the absolute abundances of Pelobacter and Dehalobacter, most notably in the α-HCH and δ-HCH cultures. Cultivation with a different HCH isomer resulted in distinct bacterial communities, but similar archaeal communities. This study provides the first direct comparison of shifts in anaerobic microbial communities induced by the dechlorination of distinct HCH isomers. It also uncovers candidate microorganisms responsible for the dechlorination of α-, ß-, γ-, and δ-HCH, a key step toward better understanding and monitoring of natural attenuation processes and improving bioremediation technologies for HCH-contaminated sites.