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Dynamic evolution of microbial colonization on indoor microplastics: polymer diversity-driven co-occurrence networks and health risks
Summary
Researchers simulated 90 days of indoor microplastic exposure to study how different polymer types, aging, and morphology influence microbial colonization on microplastic surfaces. They found that polymer diversity shaped microbial co-occurrence networks and that the resulting plastisphere communities harbored potential human pathogens.
Microplastics (MPs), as ubiquitous contaminants in indoor environments, pose health risks to humans through microbial colonization on their surfaces. This study systematically investigated the influence of MPs diversity (polymer type, aging, and morphological characteristics) on microbial colonization processes by simulating long-term exposure (90 days) in indoor air environments. Results demonstrate that aging significantly modulates initial microbial attachment by altering MPs surface properties (Brunauer-Emmett-Teller (BET) surface area increased by 32.5%-60.1%, carbonyl index elevated 0.78-2.12-fold), with biodegradable polylactide (PLA) promoting biofilm formation due to its degradation characteristics (C/O ratio increased by 20.3%). Genus-level co-occurrence network analysis revealed that symbiotic networks on MPs surfaces were unstable and fragile, being influenced by polymer type, colonization duration, and MPs diversity, thereby facilitating potential pathogenic bacteria transmission (e.g., Burkholderia, Stenotrophomonas). Mixed MPs exhibited enhanced adaptability with reduced modularity, where potential pathogenic bacteria became keystone nodes connecting modules. Furthermore, surface concentrations of phthalate esters (PAEs) on MPs increased significantly with exposure time (dibutyl phthalate (DBP), diethyl phthalate (DEP), etc. rose 4.1-40.2 fold). This study elucidates the synergistic "surface properties-co-occurrence network-potential pathogenic bacteria " mechanism through which indoor MPs amplify health risks, providing critical scientific basis for developing material property-based risk stratification strategies (e.g., classifying MPs mixtures as high-risk combinations).
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