APHL 2022 POSTER ABSTRACTS
California , San Diego ( UCSD ). We achieved > 95 % 20x coverage for samples with Ct values up to 35 with a one-day turnaround time . Using a sample de-mixing tool , Freyja , ( https :// www . medrxiv . org / content / 10.1101 / 2021.12.21.21268143v1 ), we identified mixed strains matching expected percentages , with sensitivity as low as 1 %. The automated workflow of the Genexus Integrated Sequencer enables quick turnaround times of one day with minimal hands-on time , which is ideal for high-frequency SARS-CoV-2 surveillance with wastewater samples .
For Research Use Only . Not for use in diagnostic procedure .
Presenter : Jingwei Ni , Thermo Fisher Scientific , jingwei . ni @ thermofisher . com
Identification and Quantification of Bioactive Compounds Suppressing SARS-CoV-2 in Wastewater using Metabolomic Approach
M Bayati 1 , C Li 1 , S-Y Hsu 1 , H-YHsieh 1 , L Wilfing 1 , J Klutts 2 , S Zemmer 2 , M Reynolds 3 , E Semkiw 3 , H-Y Johnson 3 , T Foley 4 , C Wieberg 2 , J Wenzel 3 , M Johnson 1 , C-H Lin 1 ; 1 University of Missouri , 2 Missouri Department of Natural Resources , 3 Missouri Department of Health and Senior Services , 4 Missouri Department of Corrections
Understanding the full scope of the COVID-19 pandemic is an ongoing challenge for public-health officials . Diagnostic testing capacity may be insufficient ; hospitalization lag infections by weeks and do not report on people with mild or asymptomatic disease . With all the limitations , wastewater-based epidemiology ( WBE ) has been used as a potential tool for assessing and managing the pandemic . In our study , SARS-CoV-2 viral material has been detected in raw wastewater throughout the COVID-19 pandemic and a positive relationship has been found between the amount of viral material in sewage and the number of reported COVID-19 cases in the area that collects and treats wastewater for a community , called a “ sewershed .” Although there is a clear correlation between the number of COVID patients in a sewershed and the level of viral material in the wastewater , there is also a clear variability among treatment facilities . Specifically , some facilities have low recovery in viral material per diagnosed case ( suggesting suppression of the genetic material from the sewershed ). Therefore , the wastewater samples were tested with UPLC-HRMS , the raw data were processed with XCMS online platform , and the features were annotated using METLIN library , which resulted in the putative identification of 30 compounds . The LC-MS / MS analyses with authentic standards was used for the absolute quantification of the compounds identified in the first approach . Fourteen compounds out of thirty have been detected and quantified . Finally , four compounds were used for suppression experiments and the results confirmed their responsibility in suppressing the genetic material in the wastewater .
Presenter : Mohamed Bayati , University of Missouri , mbb229 @ mail . missouri . edu
Biomarkers Selection for Population Normalization in SARS- CoV-2 Wastewater-based Epidemiology
S-Y Hsu 1 , M Bayati 1 , C Li 1 , H-Y Hsieh 1 , A Belenchia 2 , J Klutts 3 , S Zemmer 3 , M Reynolds 2 , E Semkiw 2 , H-Y Johnson 2 , T Foley 4 , C Wieberg 3 , J Wenzel 2 , M Johnson 1 , C-H Lin 1 ; University of Missouri ,
2
Missouri Department of Health and Senior Services , 3 Missouri Department of Natural Resources
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 human fecal biomarkers in wastewater can be critical for interpreting SARS-CoV-2 load , comparing viral load between sewage samples over time and identifying the vulnerable communities . In this study , five population biomarkers , caffeine ( CAF ), its major metabolite paraxanthine ( PARA ), creatinine ( CRE ), 5-hydroxyinoleacetic acid ( 5-HIAA ) and pepper mild mottle virus ( pMMoV ) in the wastewater were investigated for their utility for normalizing the SARS-CoV-2 loads . Their utility for estimating the real-time population contributing to the wastewater were also assessed for future WBE applications . The best candidate identified from this study was further assessed for its capacity for improving the correlation between normalized SARS-CoV-2 loads per capita and the clinic cases reported in the City of Columbia , Missouri , a university town and a community with constantly fluctuated population . Our results showed that PARA is the most reliable population biomarker for determining the SARS-CoV-2 load per capita due to its higher accuracy , lower variability , higher stability , excellent recovery rates and higher temporal consistency to reflect the change in population dynamics and dilution in wastewater . Both direct and indirect normalization approaches derived from the regression functions allow accounting for the changes in wastewater dilution and differences in relative human waste input over time without the requirement of flowrate and population at given WWTP . The PARA also demonstrates its excellent utility for real-time assessment of population contributing to the wastewater . Finally , the correlation between SARS-CoV-2 load per capita and prevalence data per capita normalized by PARAestimated population was significantly improved ( rho = 0.5878 ) suggesting that the population dynamics determined by a reliable biomarker should be always taken into the consideration for the SARS-CoV-2 WEB . The chemical marker PARA offers an excellent alternative to the currently recommended pMMoV genetic marker to help us understand the size , distribution and dynamics of local populations for forecasting the prevalence of SARS-CoV-2 within each sewershed .
Presenter : Shu-Yu Hsu , University of Missouri , shgm5 @ umsystem . edu
COVID-19