Patterns of antimicrobial resistance genes in pathogens across One Health sectors in Ireland: an in silico approach.

Abstract

As part of a rapid risk assessment, an in silico approach was used to detect antimicrobial resistance (AMR) in pathogenic isolates from humans, animals, and the environment. A total of 11,670 genomic data sets were retrieved from the NCBI Pathogen Detection system for Ireland, which represented 47 pathogenic species, including Salmonella enterica, Escherichia coli/Shigella spp., Staphylococcus aureus, Klebsiella pneumoniae, and Enterococcus faecium. Identifying the most critical pathogenic strains over time is essential, as these organisms significantly contribute to mortality, morbidity, and hospitalization. The analysis identified 799 antimicrobial resistance genes (ARGs), including their allelic diversity, 117 plasmid replicons, and 274 virulence factors. Several critical ARGs, particularly those conferring resistance to beta-lactams, aminoglycosides, quinolones, and colistin, were common across isolates originating from human, animal, and environmental sources, suggesting shared resistance profiles across One Health sectors. Klebsiella pneumoniae, E. coli/Shigella spp., S. enterica, and S. aureus were the dominant hosts of these ARGs and associated mobile genetic elements. Increasing resistance across major antibiotic classes aligned with trends reported across other European countries. This study provides a national-scale in silico comparison of AMR across pathogens and One Health sectors using publicly available genomic data. The findings help reinforce Ireland's AMR surveillance by showing which resistance genes are present and how they spread across critical pathogens in humans, animals, and the environment. These findings highlight the urgent need for improved antibiotic stewardship and integrated One Health surveillance to limit the emergence and spread of AMR.IMPORTANCEAntimicrobial resistance (AMR) is a growing threat to human, animal, and environmental health. This study used publicly available genomic data to identify antimicrobial resistance genes (ARGs) in key bacterial pathogens circulating in Ireland. By analyzing over 11,000 genomes from humans, animals, and the environment, we found that several dangerous resistance genes, including those against last-resort antibiotics, were widespread across different sources. The study highlights which bacteria and resistance genes are most critical and how they may spread between humans, animals, and the environment. These insights provide a national snapshot of AMR, supporting more effective monitoring and prevention strategies. By revealing patterns of resistance and modes of transmission, our findings underscore the importance of coordinated antibiotic stewardship and One Health approaches to slow the emergence and spread of resistant infections, protecting public health and ensuring antibiotics remain effective.