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Environmental pollutants as modifiers of antimicrobial resistance risk across food systems: a One Health perspective
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Antibiotic resistant bacteria don't just come from overusing antibiotics, everyday pollutants like metals, pesticides, and microplastics in our food and water systems may also help resistant germs survive and spread. This review argues that just because pollution could theoretically boost resistance doesn't prove it's harming people, scientists need to trace the full path from pollution to your plate before sounding the alarm.
Antimicrobial resistance (AMR) in bacteria associated with food systems is commonly attributed to antimicrobial use in clinical medicine and animal production, yet food-production and processing environments are also exposed to metals, biocides, pesticides, pharmaceutical residues, microplastics, sewage, and industrial effluents. These pressures can influence bacterial survival, biofilm persistence, antimicrobial susceptibility, and the maintenance or transfer of resistance determinants across soil, water, animals, crops, processing environments, markets, and households. This Perspective considers environmental pollutants as modifiers of AMR risk rather than sufficient evidence of causation or clinically relevant human transmission. Public-health concern is greatest where four elements converge: selective pollutant pressure, viable pathogens or clinically relevant colonizing or opportunistic organisms, mobile or expressed resistance determinants, and a credible human exposure pathway. This convergence model complements established One Health surveillance frameworks by explicitly linking environmental chemistry and pollutant mixtures with viability, resistance phenotype, mobile-element context, exposure, source attribution, and intervention evaluation. Evidence from antibiotic residues, metals, pesticides, biocides, microplastics, wastewater, genomic surveillance, and source-attribution studies indicates that biological plausibility alone is insufficient to establish human health risk. A pathway-based interpretation can distinguish environmental AMR signals from those supported by stronger evidence of food-system exposure and clinical relevance, while identifying surveillance and intervention priorities that can be tested across settings.
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