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 patient's 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 h 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.

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Owing to human activities, a large number of organic chemicals including petroleum products, industrial solvents, pesticides, herbicides (including atrazine [ATR]), and pharmaceuticals contaminate soil and aquatic environments. Remediation of these pollutants by conventional approaches is both technically and economically challenging. Bacillus endospores are highly resistant to most physical assaults and are capable of long-term persistence in soil. Spores can be engineered to express on their surface important enzymes for bioremediation purposes. We have developed a Bacillus thuringiensis spore platform system that can display a high density of proteins on the spore surface. The spore surface-tethered enzymes exhibit enhanced activity and stability relative to free enzymes in soil and water environments. In this study, we evaluated a Bacillus thuringiensis spore-display platform as a bioremediation tool against ATR. The Pseudomonas sp. strain ADP atzA determinant, an ATR chlorohydrolase important to the detoxification of ATR, was expressed as a fusion protein linked to the attachment domain of the BclA spore surface nap layer protein and expressed in B. thuringiensis. Spores from this strain are decorated with AtzA N-terminally linked on the surface of the spores. The recombinant spores were assayed for ATR detoxification in liquid and soil environments and enzyme kinetics and stability were assessed. We successfully demonstrated the utility of this spore-based enzyme display system to detoxify ATR in water and laboratory soil samples. IMPORTANCE Atrazine is one of the most widely applied herbicides in the U.S. Midwestern states. The long environmental half-life of atrazine has contributed to the contamination of surface and ground water by atrazine and its chlorinated metabolites. The toxic properties of ATR have raised public health and ecological concerns. However, remediation of ATR by conventional approaches has proven to be costly and inefficient. We developed a novel B. thuringiensis spore platform system that is capable of long-term persistence in soil and can be engineered to surface express a high density of enzymes useful for bioremediation purposes. The enzymes are stably attached to the surface of the spore exosporium layer. The spore-based system will likely prove useful for remediation of other environmental pollutants, as well.

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.

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