Your browser doesn't support javascript.
loading
Identification and Quantification of Bioactive Compounds Suppressing SARS-CoV-2 Signals in Wastewater-based Epidemiology Surveillance
Mohamed Bayati; Hsin-Yeh Hsieh; Shu-Yu Hsu; Elizabeth Rogers; Anthony Belenchia; Sally A. Zemmer; Todd Blanc; Cindy LePage; Jessica Klutts; Melissa Reynolds; Elizabeth Semkiw; Hwei-Yiing Johnson; Trevor Foley; Chris G. Wieberg; Jeff Wenzel; Terri Lyddon; Mary LePique; Clayton Rushford; Braxton Salcedo; Kara Young; Madalyn Graham; Reinier Suarez; Anarose Ford; Zhentian Lei; Lloyd Sumner; Brian P. Mooney; Xing Wei; C. Michael Greenlief; Marc Johnson; Chung-Ho Lin.
Affiliation
  • Mohamed Bayati; University of Missouri
  • Hsin-Yeh Hsieh; University of Missouri
  • Shu-Yu Hsu; University of Missouri
  • Elizabeth Rogers; University of Missouri
  • Anthony Belenchia; Missouri Department of Health and Senior Services
  • Sally A. Zemmer; Missouri Department of Natural Resources
  • Todd Blanc; Missouri Department of Natural Resources
  • Cindy LePage; Missouri Department of Natural Resources
  • Jessica Klutts; Missouri Department of Natural Resources
  • Melissa Reynolds; Missouri Department of Health and Senior Services
  • Elizabeth Semkiw; Missouri Department of Health and Senior Services
  • Hwei-Yiing Johnson; Missouri Department of Health and Senior Services
  • Trevor Foley; Missouri Department of Corrections
  • Chris G. Wieberg; Missouri Department of Natural Resources
  • Jeff Wenzel; Missouri Department of Health and Senior Services
  • Terri Lyddon; University of Missouri
  • Mary LePique; University of Missouri
  • Clayton Rushford; University of Missouri
  • Braxton Salcedo; University of Missouri
  • Kara Young; University of Missouri
  • Madalyn Graham; University of Missouri
  • Reinier Suarez; University of Missouri
  • Anarose Ford; University of Missouri
  • Zhentian Lei; University of Missouri
  • Lloyd Sumner; University of Missouri
  • Brian P. Mooney; University of Missouri
  • Xing Wei; University of Missouri
  • C. Michael Greenlief; University of Missouri
  • Marc Johnson; University of Missouri
  • Chung-Ho Lin; University of Missouri
Preprint in English | medRxiv | ID: ppmedrxiv-22272155
ABSTRACT
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.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Observational study / Prognostic study / Systematic review Language: English Year: 2022 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Observational study / Prognostic study / Systematic review Language: English Year: 2022 Document type: Preprint
...