Unraveling the origins of mobile antibiotic resistance genes using random forest classification of large-scale genomic data

Artikel i vetenskaplig tidskrift, 2025

Understanding in which environments and under what conditions chromosomal antibiotic resistance genes (ARGs) acquire increased mobility is crucial to effectively mitigate their emergence in and dissemination among pathogens. In order to identify the conditions and environments facilitating these processes, it is valuable to know from which bacterial species mobile ARGs were mobilized initially, before their dissemination to other species. In this study, we used data generated from > 1.5 million publicly available bacterial genome assemblies to train a random forest classifier to identify the origins of mobile genes. Analysis of the models’ predictions revealed the previously unknown origins of 12 mobile ARG groups, which confer resistance to 4 different classes of antibiotics. This included ARGs conferring resistance to tetracyclines, an antibiotic class for which, to the best of our knowledge, no recent origins of ARGs have previously been convincingly demonstrated. All identified origin species in this study are known opportunistic pathogens, and some are the origin of multiple mobile ARGs. An analysis of public metagenomes from different sources indicates that most of the origin species are particularly abundant in municipal wastewaters, a few were highly abundant in animal feces and three were most common in environments polluted with waste from antibiotic manufacturing. This study highlights environments where these origin species thrive and where there is a need for limiting antibiotic selection pressures.