Metric-dependent effects of microplastics on environmental antibiotic resistomes

Microplastics (MPs) are increasingly implicated in shaping environmental resistomes, yet their effects on antibiotic resistance genes (ARGs) remain difficult to compare across metrics and settings. Here, we synthesise 1148 observations to quantify how MPs influence ARG abundance under controlled exposure. Effect sizes were calculated as log response ratios (lnRR), with percentage changes presented as back-transformed values derived from lnRR estimates. We explicitly separate relative (community-normalised) and absolute (copy-number-based) abundance to distinguish compositional shifts from changes in total gene load. We then evaluate how environmental matrix, exposure duration, particle size, concentration, and polymer type modify these responses. MP addition boosts relative ARG abundance, especially for β-lactam (213%), sulfonamide (205%), and aminoglycoside (123%) resistance, while absolute-abundance responses are weaker and more variable, with declines in chloramphenicol (-73%) and fluoroquinolone (-93%). Aminoglycoside is the only gene family that rises consistently under both metrics. ARG responses varied strongly across environmental matrices. Seawater exhibited the strongest metric divergence, with fluoroquinolone and sulfonamide declining sharply in absolute abundance (-93% and -98%) but increasing markedly in relative abundance (865% and 363%). In contrast, soil exhibited more concordant responses, such as for tetracycline, which increased under both absolute and relative abundance. Microplastics properties further modulated ARG responses. Submicron plastics (SMPs) and MPs, medium-to-high MP concentrations and specific polymer-gene combinations such as PVC-aminoglycoside are associated with especially marked responses. Overall, our results indicate that microplastics effects on environmental ARGs are strongly metric-dependent, with relative abundance primarily capturing community restructuring rather than changes in total ARG load. These findings highlight the necessity of jointly considering abundance metrics, environmental matrices, and MP characteristics when interpreting microplastic-associated antibiotic resistance risks.