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O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/22279459v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@debf50org.highwire.dtl.DTLVardef@1e21da2org.highwire.dtl.DTLVardef@78708org.highwire.dtl.DTLVardef@3239ee_HPS_FORMAT_FIGEXP M_FIG C_FIG The primary objective of this study was to identify a universal wastewater biomarker for population normalization for SARS-CoV-2 wastewater-based epidemiology (WBE). A total of 2,624 wastewater samples (41 weeks) were collected weekly during May 2021-April 2022 from 64 wastewater facilities across Missouri, U.S. Three wastewater biomarkers, caffeine and its metabolite, paraxanthine, and pepper mild mottle virus (PMMoV), were compared for the population normalization effectiveness for wastewater SARS-CoV-2 surveillance. Paraxanthine had the lowest temporal variation and strongest relationship between population compared to caffeine and PMMoV. This result was confirmed by data from ten different Wisconsins WWTPs with gradients in population sizes, indicating paraxanthine is a promising biomarker of the real-time population across a large geographical region. The estimated real-time population was directly compared against the population patterns with human movement mobility data. Of the three biomarkers, population normalization by paraxanthine significantly strengthened the relationship between wastewater SARS-CoV-2 viral load and COVID-19 incidence rate the most (40 out of 61 sewersheds). Caffeine could be a promising population biomarker for regions where no significant exogenous caffeine sources (e.g., discharges from food industries) exist. In contrast, PMMoV showed the highest variability over time, and therefore reduced the strength of the relationship between sewage SARS-CoV-2 viral load and the COVID-19 incidence rate, as compared to wastewater data without population normalization and the population normalized by either recent Census population or the population estimated based on the number of residential connections and average household size for that municipality from the Census. Overall, the findings of this long-term surveillance study concluded that the paraxanthine has the best performance as a biomarker for population normalization for SARS-CoV-2 wastewater-based epidemiology.
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Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the SARS-CoV-2 levels in the communities since the COVID-19 outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater can be critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (pMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated for their utility in normalizing the SARS-CoV-2 loads through developed direct and indirect approaches. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performed candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuated population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population at any given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation (rho=0.5878, p<0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker offers an excellent alternative to the currently CDC-recommended pMMoV genetic biomarker to help us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed. HIGHLIGHT (bullet points)O_LIThe paraxanthine (PARA), the metabolite of the caffeine, is a more reliable population biomarker in SARS-CoV-2 wastewater-based epidemiology studies than the currently recommended pMMoV genetic marker. C_LIO_LISARS-CoV-2 load per capita could be directly normalized using the regression functions derived from correlation between paraxanthine and population without flowrate and population data. C_LIO_LINormalizing SARS-CoV-2 levels with the chemical marker PARA significantly improved the correlation between viral loads per capita and case numbers per capita. C_LIO_LIThe chemical marker PARA demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. C_LI
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Recent SARS-CoV-2 wastewater-based epidemiology (WBE) surveillance have documented a positive correlation between the number of COVID-19 patients in a sewershed and the level of viral genetic material in the wastewater. Efforts have been made to use the wastewater SARS-CoV-2 viral load to predict the infected population within each sewershed using a multivariable regression approach. However, reported clear and sustained variability in SARS-CoV-2 viral load among treatment facilities receiving industrial wastewater have made clinical prediction challenging. Several classes of molecules released by regional industries and manufacturing facilities, particularly the food processing industry, can significantly suppress the SARS-CoV-2 signals in wastewater by breaking down the lipid-bilayer of the membranes. Therefore, a systematic ranking process in conjugation with metabolomic analysis was developed to identify the wastewater treatment facilities exhibiting SARS-CoV-2 suppression and identify and quantify the chemicals suppressing the SARS-COV-2 signals. By ranking the viral load per diagnosed case among the sewersheds, we successfully identified the wastewater treatment facilities in Missouri, USA that exhibit SARS-CoV-2 suppression (significantly lower than 5 x 1011 gene copies/reported case) and determined their suppression rates. Through both untargeted global chemical profiling and targeted analysis of wastewater samples, 40 compounds were identified as candidates of SARS-CoV-2 signal suppression. Among these compounds, 14 had higher concentrations in wastewater treatment facilities that exhibited SARS-CoV-2 signal suppression compared to the unsuppressed control facilities. Stepwise regression analyses indicated that 4-nonylphenol, palmitelaidic acid, sodium oleate, and polyethylene glycol dioleate are positively correlated with SARS-CoV-2 signal suppression rates. Suppression activities were further confirmed by incubation studies, and the suppression kinetics for each bioactive compound were determined. According to the results of these experiments, bioactive molecules in wastewater can significantly reduce the stability of SARS-CoV-2 genetic marker signals. Based on the concentrations of these chemical suppressors, a correction factor could be developed to achieve more reliable and unbiased surveillance results for wastewater treatment facilities that receive wastewater from similar industries.
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SARS-CoV-2 genetic material has been detected in raw wastewater around the world throughout the COVID-19 pandemic and has served as a useful tool for monitoring community levels of SARS-CoV-2 infections. SARS-CoV-2 genetic material is highly detectable in a patients feces and the household wastewater for several days before and after a positive COVID-19 qPCR test from throat or sputum samples. Here, we characterize genetic material collected from raw wastewater samples and determine recovery efficiency during a concentration process. We find that pasteurization of raw wastewater samples did not reduce SARS-CoV-2 signal if RNA is extracted immediately after pasteurization. On the contrary, we find that signal decreased by approximately half when RNA was extracted 24-36 hours post-pasteurization and [~]90% when freeze-thawed prior to concentration. As a matrix control, we use an engineered enveloped RNA virus. Surprisingly, after concentration, the recovery of SARS-CoV-2 signal is consistently higher than the recovery of the control virus leading us to question the nature of the SARS-CoV-2 genetic material detected in wastewater. We see no significant difference in signal after different 24-hour temperature changes; however, treatment with detergent decreases signal [~]100-fold. Furthermore, the density of the samples is comparable to enveloped retrovirus particles, yet, interestingly, when raw wastewater samples were used to inoculate cells, no cytopathic effects were seen indicating that wastewater samples do not contain infectious SARS-CoV-2. Together, this suggests that wastewater contains fully intact enveloped particles.
