Molecular insights into antimicrobial resistance in human bacterial pathogens: mechanisms, resistance genes, and...

Antimicrobial resistance (AMR) represents one of the most critical global public health challenges. This review provides a comprehensive overview of the molecular foundation of AMR in human bacterial pathogens, including the biology of resistance genes and the importance of the mobile genetic elements-plasmids, transposons, and integrons-in facilitating the rapid horizontal transfer of resistance determinates across the populations. We critically evaluate current and emerging molecular diagnostic platforms - including targeted polymerase chain reaction (PCR), whole-genome sequencing (WGS), clustered regularly interspaced short palindromic repeats (CRISPR)-based technologies, and metagenomics - emphasizing their comparative performance, limitations, and suitability for point-of-care deployment. The review addresses the translational integration of molecular diagnostics into antimicrobial stewardship programmes and real-time AMR surveillance, with particular attention to the persistent gap between laboratory-generated genomic data and actionable clinical decision-making. Emerging evidence suggests that artificial intelligence (AI) and machine learning hold considerable promise for improving resistance phenotype prediction from genomic data and informing personalized antibiotic therapy, although widespread clinical implementation remains in its early stages. The transition from phenotypic to genotypic strategies represents a significant paradigm shift in AMR, with the potential to substantially improve surveillance, diagnostic accuracy, and therapeutic outcomes, provided that outstanding barriers in infrastructure, standardization, and equity are addressed.