Resolving the Genomic Context of Clinically Relevant Antibiotic Resistance Genes in Wastewater with Ligation-Mediated PCR

Abstract Antimicrobial resistance (AMR) is a pressing global public health challenge. AMR is driven in part by the spread of antibiotic resistance genes (ARGs) through bacterial communities via mobile genetic elements. Influent wastewater is a promising sample type for monitoring AMR because it pools biological inputs shed by individuals across a population. However, untargeted sequencing approaches, such as metagenomic sequencing, often miss low-abundance targets such as clinically important ARGs. In this work, we develop a ligation-mediated PCR (LM-PCR) enrichment strategy that can directionally capture the genomic context surrounding an ARG using long-read sequencing. We applied this method to study the natural genomic context diversity of four clinically relevant ARGs (blaCTX-M, blaKPC, and blaOXA-48-like, and qnrS) across 13 wastewater treatment plants in Washington state, each sampled at two timepoints. Across all timepoints, LM-PCR identified distinct genomic context cluster families associated with each ARG, including seven for blaKPC, 11 for blaCTX-M, 24 for qnrS, and one for blaOXA-48-like. Notably, 11 of the 24 qnrS containing clusters were putatively novel, with no matches to existing sequences in public databases. Genomic contexts associated with blaCTX-M and blaKPC were comparatively conserved across clusters, whereas qnrS was associated with a more diverse set of genetic sequences. Together, these results demonstrate that LM-PCR can resolve low-abundance, ARG-associated genomic variation in complex wastewater samples and provide a scalable framework for tracking the dissemination of clinically relevant AMR determinants.