Development and Optimization of Virus Concentration and Detection Methods for tracking SARS-CoV-2 and its Variants in wastewater

Doctoral Candidate Name: 
Md Ariful Islam Juel
Program: 
Civil Engineering
Abstract: 

Wastewater-based epidemiology (WBE) has drawn significant attention as an early warning tool to detect and predict the trajectory of COVID-19 cases in a community, in conjunction with public health data. This means of monitoring for outbreaks has been used at municipal wastewater treatment centers to analyze COVID-19 trends in entire communities, as well as by universities and other community living environments to monitor COVID-19 spread in buildings. Precise and accurate quantification of viral copies in wastewater is a prerequisite for a successful WBE surveillance project. Accurate quantification of SARS-CoV-2 is dependent on the choice of an effective and reliable virus concentration method. Sample concentration is crucial, especially when viral abundance in raw wastewater is below the threshold of detection by RT-qPCR analysis. The first objective of my dissertation is the performance evaluation of a rapid ultrafiltration-based virus concentration method using InnovaPrep Concentrating Pipette (CP) Select and how it compares with the electronegative membrane filtration (HA) method. The criteria of the evaluation were based on the SARS-CoV-2 detection sensitivity, surrogate virus recovery rate, and sample processing time. Results suggested that the CP Select concentrator was more efficient at concentrating SARS-CoV-2 from wastewater compared to the HA method. About 25% of samples that tested SARS-CoV-2 negative when concentrated with the HA method produced a positive signal with the CP Select protocol. The optimization of the CP Select protocol by adding AVL lysis buffer and sonication increased Bovine Coronavirus (BCoV) recovery by 19%, which seems to compensate for viral loss during centrifugation. Filtration time decreased by approximately 30% when using the CP Select protocol, making this an optimal choice for building surveillance applications where quick turnaround time is necessary.

The inherent limitation of most of the current virus concentration methods is capable of processing small volumes of wastewater ranging from 20 – 250 mL. While small volume-based virus concentration methods can be successful for detecting and quantifying SARS-CoV-2 viruses during high community infection, these methods may not be informative, especially during the early stage of community infections. The second objective is to develop a large-volume filtration-based virus concentration method for increased sensitivity of molecular detection of SARS-CoV-2 and application in sequencing techniques. A dead-end hollow fiber ultrafilter (UF) and electronegative membrane filtration (HA) were used as primary and secondary concentration methods for concentrating viruses from wastewater. This study found that a modified UF-HA method, incorporating sonication and centrifugation, showed 100% SARS-CoV-2 positive detection in low COVID-19 infection periods compared to only 9% positive detection with the HA method and 63% with the UF alone. During the high COVID-19 infection period, no significant difference in SARS-CoV-2 detection and quantification was observed among the alternatives. The hollow UF-based primary method showed higher BCoV recovery compared to the combined method and HA method. The combined method (UF-HA_soni) can be used to identify the early stages of COVID-19 infection by detecting SARS-CoV-2 viruses from the low-tittered wastewater which can help prevent future outbreaks. Either the combined method or the UF-based primary method can be used to monitor SARS-CoV-2 viruses during the high COVID-19 infection period.

We also aim to apply digital droplet PCR to track the transmission dynamics of the Omicron variants by assessing the relative proportion of the strains circulating in Charlotte, North Carolina. We applied Digital Droplet Polymerase Chain Reaction (ddPCR) technology to detect and quantify Omicron variants using three different mutation assays targeting the S gene (N764K and N856K). Using these two assays, we first detected the Omicron variants on December 6, 2021, from the wastewater sample of Mecklenburg County which was earlier than the first clinical detection on December 10, 2021. The relative abundance of Omicron VOCs determined by the RT-ddPCR from wastewater was strongly and positively correlated with the clinically reported VOCs (r = 0.98, p = < 0.0001). This surveillance method for the variant analysis can give a near real-time transmission dynamic of the Omicron variants enabling quick administrative intervention such as awareness, preparedness, and control measures.

Defense Date and Time: 
Wednesday, November 8, 2023 - 2:30pm
Defense Location: 
EPIC 3344
Committee Chair's Name: 
Mariya Munir
Committee Members: 
Cynthia Gibas, Olya Keen, Jessica Schlueter