Treatment of nonwoven polypropylene to increase adsorption of SARS-CoV-2 spike protein

The COVID-19 pandemic caused by the respiratory transmission of the SARS-CoV-2 virus has resulted in millions of deaths. While the production of a vaccine has greatly reduced mortality and hospitalization where available, lack of vaccine availability and mutations of the virus render masking a vital strategy for reducing the spread of disease. Increasing the efficacy of a mask to adsorb the virus has significant potential to reduce disease spread. Nonwoven polypropylene (PP) is used as a filtration layer in N-95 masks and other over the counter masks. To increase the adsorption of the virus, the nonwoven PP layer was treated with oxygen plasma, polyethylene glycol (PEG), and hyaluronic acid (HA). The treated materials were evaluated over one month and found to increase adsorption of the spike protein on the surface of the SARS-CoV-2 virion.

Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) levels in the communities since the coronavirus disease 2019 (COVID-19) outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater is 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 and validated for their utility in normalizing the SARS-CoV-2 loads through two normalizing approaches using the data from 64 wastewater treatment plants (WWTPs) in Missouri. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performing 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 fluctuating 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 of the 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 complements the current normalization scheme recommended by CDC and helps us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

Identification and quantification of bioactive compounds suppressing SARS-CoV-2 signals in wastewater-based epidemiology surveillance.

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 × 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 suppressors. 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.

A novel colorimetric biosensor for detecting SARS-CoV-2 by utilizing the interaction between nucleocapsid antibody and spike proteins

SARS-CoV-2 is a pandemic coronavirus that causes severe respiratory disease (COVID-19) in humans and is responsible for millions of deaths around the world since early 2020. The virus affects the human respiratory cells through its spike (S) proteins located at the outer shell. To monitor the rapid spreading of SARS-CoV-2 and to reduce the deaths from the COVID-19, early detection of SARS-CoV-2 is of utmost necessity. This report describes a flexible colorimetric biosensor capable of detecting the S protein of SARS-CoV-2. The colorimetric biosensor is made of polyurethane (PU)-polydiacetylene (PDA) nanofiber composite that was chemically functionalized to create a binding site for the receptor molecule—nucleocapsid antibody (anti-N) protein of SARS-CoV-2. After the anti-N protein conjugation to the functionalized PDA fibers, the PU-PDA-NHS-anti fiber was able to detect the S protein of SARS-CoV-2 at room temperature via a colorimetric transition from blue to red. The PU-PDA nanofiber-based biosensors are flexible and lightweight and do not require a power supply such as a battery when the colorimetric detection to S protein occurs, suggesting a sensing platform of wearable devices and personal protective equipment such as face masks and medical gowns for real-time monitoring of virus contraction and contamination. The wearable biosensors could significantly power mass surveillance technologies to fight against the COVID-19 pandemic. Graphical Supplementary Information The online version contains supplementary material available at 10.1007/s44164-022-00022-z.

Defining biological and biophysical properties of SARS-CoV-2 genetic material in wastewater.

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.