Antimicrobial resistance poses a fundamental threat to global public health. Robust public health surveillance is necessary to track its spread and inform antimicrobial stewardship practices, but current surveillance relies heavily on clinical screening and is therefore biased and limited in scope. Wastewater-based epidemiology has emerged as a promising tool for monitoring community-level infectious disease trends, offering a less biased method for surveillance of the communal resistome. Genomic sequencing of the wastewater allows for detailed characterization of the local resistome; however, antibiotic resistance genes typically represent a minute fraction of the total DNA in wastewater, making them challenging and expensive to sequence through traditional shotgun approaches. Consequently, few longitudinal wastewater resistome studies with high sampling densities exist. Targeted enrichment of these genes prior to sequencing is necessary to improve sensitivity and reduce costs. Hybridization probe capture addresses this by introducing oligonucleotides that hybridize with and retain target DNA, allowing for the depletion of background material. This thesis details the development of an end-to-end targeted sequencing workflow tailored to the detection of antibiotic resistance genes in municipal wastewater. A custom probe panel is validated in silico and in vitro using a mock microbial community. Finally, the optimized workflow is applied to a year-long longitudinal surveillance study across four urban wastewater treatment plants. This thesis reports on seasonal shifts in resistance, describes the relationship between resistome composition with clinical antibiotic usage, and profiles high-priority resistance gene threats, demonstrating the utility of probe capture for sensitive environmental surveillance.
Liam Byrne (Thu,) studied this question.