Quantifying antibiotic resistome risks across environmental niches: the L-ARRAP for long-read metagenomic profiling.

Abstract

The global dissemination of antibiotic resistance genes (ARGs) represents a critical challenge to One Health. Existing ARG risk assessment tools (e.g. MetaCompare, ARRI) are constrained by short-read sequencing data, limiting their utility for long-read platforms. To address this gap, we developed the Long-read based Antibiotic Resistome Risk Assessment Pipeline (L-ARRAP), which calculates the Long-read based Antibiotic Resistome Risk Index (L-ARRI) to quantify antibiotic resistome risks. Building upon our previous ARRI framework, L-ARRAP leverages long-read sequencing advantages to concurrently identify ARGs, mobile genetic elements, and human bacterial pathogens, integrating their interactions for risk scoring. Our results showed that L-ARRAP was not only able to accurately identify ARGs and evaluate the antibiotic resistance risk scores in samples of hospital wastewater (HWW), Chaohu lake, and human fecal samples, but also significantly distinguish the ARG risk in HWW samples between before and after disinfection groups, demonstrating the performance of L-ARRAP. Furthermore, L-ARRAP scores exhibited strong concordance with those generated by our laboratory-adapted MetaCompare variant (L-MetaCompare), corroborating its methodological reliability. Overall, to our knowledge, L-ARRAP is the first assessment pipeline of antibiotic resistome for long sequencing reads and has a great potential for monitoring the risk of ARGs in various environmental niches.