Human-associated microbial inputs and bacterial-fungal ecological coupling shape antibiotic resistance risk in environmental dust.

Environmental dust represents a critical exposure matrix, yet the relationships between multi-kingdom dust microbiomes and antimicrobial resistance (AMR)-associated health risks remain insufficiently characterized. We applied shotgun metagenomics to dust samples from pharmaceutical factories, a dairy farm, railway stations, and schools to comprehensively characterize bacterial, fungal, and viral communities, alongside resistome structure. Microbial community composition exhibited significant differences across all three domains among the sampled environments. Specifically, dust from railway stations displayed the strongest human-associated microbial signal and harbored the highest diversity of antibiotic resistance genes (ARGs), and MetaCompare-derived AMR risk. Functional analyses revealed shared bacterial-fungal metabolic organization, with cross-domain taxonomic and functional associations pointing to structured ecological coupling. Variation partitioning analysis showed that shared explanatory components accounted for most of the variation in MetaCompare-based human-health AMR risk, particularly the overlap among bacterial composition, humanization, and fungal functional structure. Notably, Candida and Aureobasidium emerged as divergent fungal indicators, tracking microbiome humanization and resistome risk in opposite directions. By contrast, viral auxiliary metabolic genes accounted for only 3.92% of the abundance-weighted virome, consistent with a host-linked auxiliary layer rather than a dominant independent pathway. Collectively, these findings demonstrate that AMR-related signatures in environmental dust are shaped by the interplay of human-associated microbial inputs and ecologically coupled bacterial-fungal interactions.