Genetic markers of antimicrobial resistance in experimental models and surveillance systems

Background. Antimicrobial resistance (AMR) is shaped by clinical, veterinary, agricultural and environmental processes. Its analysis requires the assessment of resistance genes, experimental models, diagnostic approaches and surveillance systems that track antibiotic resistance genes (ARGs) across human, animal and environmental reservoirs.

Objective. To summarize data on experimental and computational models of ARG dissemination, characterize selected AMR markers and evaluate current methods for their detection.

Material and methods. A narrative review with a transparent search strategy and thematic synthesis was conducted. PubMed/MEDLINE, Scopus, Web of Science and Google Scholar were searched; the last search was performed on May 2, 2026. After full-text assessment, 46 sources were included.

Results. The review discusses blaCTX-M-15, blaNDM, blaKPC, blaOXA-23, floR and intI1, as well as mobile genetic elements involved in their dissemination. It summarizes the strengths and limitations of in vitro models, gut models, mouse models, biofilm systems, mathematical modelling, AST, PCR/qPCR, WGS, mNGS, machine learning and CRISPR-Cas12a diagnostics.

Conclusion. CRISPR-Cas12a platforms may support rapid targeted screening of predefined ARGs but do not replace phenotypic susceptibility testing or genome-scale analysis. The most robust strategy is the integration of AST, WGS/mNGS, targeted molecular diagnostics, machine learning and One Health surveillance.

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