Integrating global microbiome data into antibiotic resistance assessment in large rivers.

• Global microbiome data were integrated into AMR assessment in the Pearl River. • The river had a higher AMR level than global rivers, with WWTPs and landfills as major sources. • Detection of risk rank I and emerging ARGs highlighted AMR risk in some river reaches. • Pathogen-related families were predominant ARG-carrying bacteria in river water and sediment. • Co-sharing of ARGs across taxonomic ranks implied their transfer potentials in the community. Rivers are important in spreading antimicrobial resistance (AMR). Assessing AMR risk in large rivers is challenged by large spatial scale and numerous contamination sources. Integrating river resistome data into a global framework may help addressing this difficulty. Here, we conducted an omics-based assessment of AMR in a large river (i.e. the Pearl River in China) with global microbiome data. Results showed that antibiotic resistome in river water and sediment was more diversified than that in other rivers, with contamination levels in some river reaches higher than global baselines. Discharge of WWTP effluent and landfill waste drove AMR prevalence in the river, and the resistome level was highly associated with human and animal sources. Detection of 54 risk rank I ARGs and emerging mobilizable mcr and tet(X) highlighted AMR risk in the river reaches with high human population density and livestock pollution. Florfenicol-resistant floR therein deserved priority concerns due to its high detection frequency, dissimilar phylogenetic distance, mobilizable potential, and presence in multiple pathogens. Co-sharing of ARGs across taxonomic ranks implied their transfer potentials in the community. By comparing with global genomic data, we found that Burkholderiaceae, Enterobacteriaceae, Moraxellaceae and Pseudomonadaceae were important potential ARG-carrying bacteria in the river, and WHO priority carbapenem-resistant Enterobacteriaceae, A. baumannii and P. aeruginosa should be included in future surveillance. Collectively, the findings from this study provide an omics-benchmarked assessment strategy for public risk associated with AMR in large rivers. [Display omitted] [ABSTRACT FROM AUTHOR]