Drug-resistant Klebsiella pneumoniae and related Enterobacterales represent an escalating global public health threat, increasingly limiting therapeutic options in both healthcare- and community-associated infections. This review summarizes how resistance in K. pneumoniae emerges from the synergy of intrinsic barriers and acquired determinants. Key molecular mechanisms include reduced permeability via porin remodeling (notably OmpK35/OmpK36), multidrug efflux (e.g., AcrAB-TolC and OqxAB), and enzymatic drug inactivation driven by extended-spectrum beta-lactamases and carbapenemases (e.g., KPC, OXA-48-like enzymes, and metallo-beta-lactamases). We also highlight clinically meaningful pathways underlying polymyxin/colistin resistance, including mgrB inactivation and PhoPQ/PmrAB-mediated lipid A modification. In addition to stable genetic resistance, adaptive programs can shape transient tolerance and persistence, including stress responses that modulate gene expression under antibiotic and host-imposed pressures. The ability of these organisms to form biofilms, particularly on medical devices, further complicates treatment and eradication. Finally, we discuss therapeutic implications and current options and limitations—including novel beta-lactam/beta-lactamase inhibitor combinations and siderophore cephalosporins—and emphasize the importance of aligning therapy and surveillance with the underlying resistance mechanisms and circulating high-risk lineages.

Our study highlights the escalating issue of beta-lactam resistance in nosocomial pathogens, driven by the broad spectrum of antibiotic-degrading enzymes and plasmid exchange. We catalogued known beta-lactamases across 230 bacterial genera, identified 2349 potential beta-lactamases across over 673 genera, and anticipate discovering many new types, underscoring the need for targeted gene analysis in combating resistance. This study also elucidates the complex relationship between the diversity and frequency of beta-lactamase genes across bacterial genera, highlighting the need for genus-specific approaches in combating antibiotic resistance and emphasizing these genes' significant global distribution and host-specific prevalence. We report many transcriptional regulators, transposases and other factors in the genomes of 20 different bacterial isolates, some of which are consistent with the ability of these species to adapt to different environments. Although we could not determine precisely which factors regulate the presence of beta-lactamases in specific bacteria, we found that the proportion of regulatory genes, the size of the genome, and other factors are not decisive. Further studies are needed to elucidate key aspects of this process.

Background: Antimicrobial resistance is a growing global health threat, with beta-lactamases playing a central role in resistance to beta-lactam antibiotics. Building on our previous survey of 2340 putative beta-lactamases, we conducted an in-depth analysis of 129 prioritized candidates (70–98.5% amino acid identity to characterized enzymes) detected in 102 bacterial genera across 13 phylogenetic classes from environmental, animal, and human sources worldwide. Methods: We applied a motif-centric assessment of class-defining catalytic residues, evaluated the genomic context using a heuristic Index of Proximal Mobility (IPM) derived from the two immediately adjacent open reading frames, and examined the phylogenetic placement. AI-based substrate predictions were generated at a restricted scope as exploratory evidence. Results: Candidates spanned all Ambler classes (A–D); preservation of catalytic motifs was common and consistent with potential catalytic activity. Twelve of 129 (9.3%) loci had nearby mobile-element types (e.g., insertion sequences, integrases, transposases) and scored High IPM, indicating genomic contexts compatible with horizontal gene transfer. We also observed near-identical class A enzymes across multiple genera and continents, frequently adjacent to mobilization proteins. Conclusions: We propose a reproducible, bias-aware, early warning framework that prioritizes candidates based on motif integrity and mobility context. The framework complements existing surveillance (GLASS/EARS-Net) and aligns with a One Health approach integrating human, animal, and environmental reservoirs. Identity thresholds and IPM are used for inclusion and contextual prioritization, rather than as proof of function or mobility; AI-based predictions serve as hypothesis-generating tools. Experimental studies will be essential to confirm enzymatic activity, mobility, and clinical relevance.