Antimicrobial resistance surveillance: lessons learnt from large databases of antimicrobial resistance genes

Ocular infections are becoming increasingly difficult to treat as antimicrobial resistance (AMR) rises globally. Conventional resistance testing captures only a limited fraction of microbial resistance potential. This review highlights the growing role of genomic approaches—particularly whole-genome sequencing combined with large antimicrobial resistance gene (ARG) databases—in predicting phenotypic and multidrug resistance in bacterial ocular pathogens. While these tools are well developed for bacteria, their application to viral and fungal ocular infections remains limited and represents an important area for future research. Metagenomic analysis of the ocular surface microbiome is identified as a promising, rapid, and sensitive method to detect ARGs, monitor resistance trends, and identify commensal reservoirs of transferable resistance genes. Beyond diagnostics, these technologies could be used to study the long-term effects of topical antibiotics, disinfectants, and preservatives on the ocular microbiome, as well as to support epidemiological investigations into the acquisition and transmission of AMR in ocular infections.