Comprehensive Characterization of Bioaerosol Microbial Communities, ARG, and Occupational Exposure Risks in WWTP and...

In the sewage treatment plant and landfill in the same area, the differences in transmission characteristics of potential pathogenic microorganisms and antibiotic resistance genes/movable genetic elements (ARGs/MGEs) mediated by bioaerosols have not been fully studied. Therefore, we integrated 16S rRNA gene amplicon sequencing, high-throughput quantitative PCR, quantitative microbial risk assessment, exposure-dose estimation, and machine learning to compare microbial communities, antibiotic resistance genes and mobile genetic elements (ARGs/MGEs), and estimated occupational exposure levels at a wastewater treatment plant (XQ) and an integrated solid waste treatment facility (DP) in Central China. The mean culturable bacterial concentration was 3.4-fold higher at DP than at XQ (1726 CFU/m³, 502 CFU/m³), and proportion of fine biogenic particles was also higher at DP (27%, 15%). In contrast, mean airborne concentration of ARGs/MGEs was substantially higher at XQ than at DP (5462 copies/m³, 584 copies/m³), resulting in a higher estimated inhalation exposure dose at XQ. The dominant resistance determinants were ermC, dhps, and intI1 at XQ, and cmxA, tnpA-05, and lnuA-01 at DP. Machine learning analysis identified Faecalibacterium as an important microbial feature distinguishing solid waste bioaerosols, whereas blaPAO was among most influential ARG features associated with XQ bioaerosols. Partial least squares regression revealed extensive covariation between bacterial genera and resistance determinants. Achromobacter was positively associated with ermX at XQ and with intI1 at DP, although these associations do not establish direct host-gene relationships. Overall, two facilities showed contrasting bioaerosol exposure profiles, characterized by higher bacterial and fine-particle levels at DP and higher ARG/MGE exposure estimates at XQ. These findings support facility-specific occupational aerosol control and monitoring strategies.