Enhancing Wastewater Surveillance Through the Development of Novel Detection Assays for Variants of SARS-CoV-2 and Influenza Viruses

Abstract

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for the COVID-19 pandemic, has posed a significant threat to global public health. The transmission of this virus through respiratory droplets and aerosols has led to the rapid spread of infections. Since the COVID-19 pandemic outbreak started in late 2019, numerous studies have demonstrated the presence of SARS-CoV-2 viral particles or genomic RNA in bodily wastes, including feces, urine, and respiratory fluids, originating from both symptomatic and asymptomatic patients. Due to these results, wastewater surveillance has been growing as a supportive tool to monitor and determine the presence of respiratory viruses in communities. This approach can help identify the emergence of outbreaks before clinical cases are reported, allowing public health officials to take early measures to contain the spread of the virus. However, despite its potential benefits, wastewater surveillance also has some limitations that need to be addressed for accurate and effective surveillance. The overall objective of this dissertation was to enhance wastewater surveillance for enveloped respiratory viruses such as SARS-CoV-2 and influenza viruses through advancements in data adjustments and molecular analyses. First, we conducted cross-correlation analysis on time-series data of SARS-CoV-2 RNA abundance and clinical case data from two major wastewater treatment plants (WWTPs) in Honolulu, Hawaiʻi. The detection of time lags between the data was enhanced through prewhitening and population normalization strategies. Second, molecular detection inhibitors in wastewater, especially humic acid, were used to determine the inhibition effect on hydrolysis probe-based real-time polymerase chain reaction (qPCR). This indicates the significance of comprehending the inhibitory mechanism of reporter dye of hydrolysis probes in the presence of humic acid in wastewater to ensure accurate quantification of targets. Third, we developed a new nested RT-PCR-PCR method to amplify and sequence the spike (S) protein gene region of SARS-CoV-2 (532 bp), including the receptor binding domain (RBD) for mutation identification from monthly wastewater samples collected from a small residential sewershed in Honolulu, Hawai‘i since the beginning of the COVID-19 pandemic. The study aimed to determine the viability of detecting novel variants in wastewater and to evaluate the performance of removal of PCR inhibitors with the Inhibitor Removal Technology® (IRT) and internal amplification standard (IAS). Fourth, a new amplicon sequencing method was developed to simultaneously amplify 576 bp of the polymerase basic 1 (PB1) encoding gene from various influenza virus variants present in wastewater. To address amplification bias resulting from varying primer-template affinities among variants and the presence of PCR inhibitors, IASs with multiple genes and different primer-template affinities were used to evaluate the amplification bias. Collectively, the outcomes of this dissertation will illustrate the potential for enhancing wastewater surveillance of SARS-CoV-2 and influenza viruses, leading to more accurate detection of their abundance and variants in wastewater.