Antibiotic resistance genes against "last-resort" antibiotics within the One Health framework: Dissemination, mechanisms, and AI-driven opportunities.

Last-resort antibiotic resistance genes (LARGs), resistance determinants that compromise last-line antibiotics, including blaNDM, mcr and tet(X), are emerging environmental contaminants that undermine the efficacy of carbapenems, polymyxins and tigecycline. Their growing presence in wastewater, soils, sediments, livestock environments and aerosols raises concerns about environmental contamination and human exposure within the One Health context. Although originally confined to clinical settings, these determinants are now widespread across natural and engineered environments. Their dissemination is driven by insertion sequences, integrons and high-risk plasmids, while their persistence is maintained through compensatory evolution, regulatory adaptation and context-dependent fitness costs. LARGs often coexist with heavy-metal and biocide resistance genes, stress-adaptation functions and virulence factors, forming multifunctional genetic assemblages that reinforce pathogenicity, ecological resilience and zoonotic potential even at low environmental abundance. Conventional mitigation measures, including wastewater treatment, anaerobic digestion, composting and other physicochemical or biological processes, remove only part of these determinants, allowing residual genes to persist. Emerging approaches such as advanced oxidation processes, photocatalytic technologies, enhanced composting and biochar-based interventions offer improved but still incomplete removal, underscoring the need for more integrated and effective control frameworks. This study synthesizes mechanistic and ecological insights into LARGs and emphasizes artificial intelligence-enabled advances for precise detection, environmental surveillance, dissemination prediction, and optimization of mitigation strategies, providing a foundation for developing sustainable, integrative, and intelligent frameworks for resistance monitoring and control within the One Health context.