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Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
Published on: January 7, 2019
Local environment, surface characteristics and stochastic processes shape the dynamics of urban dustbin surface
Xin-Li An1, Mei-Rong Xu2, Xiao-Fang Pan1
1Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
None:
Dustbins function as critical infrastructures for urban sanitation, creating a distinct breeding ground for microbial assemblages. However, there is no information regarding the dynamics of microbial communities and the underlying mechanism for community assembly on dustbin surfaces. Here, surface samples were collected from three sampling zones (business building, commercial street and residential community) with different types (kitchen waste, harmful waste, recyclables, and others) and materials (metallic and plastic); and distribution pattern and assembly of microbial communities were investigated by high-throughput sequencing. Bacterial and fungal communities showed the distinct community variations across sampling zones and waste sorting. Core community and biomarker species were significantly correlated with the spatial distribution of overall community. The detection of pathogens highlighted the potential risk of surface microbiome. Human skin, human feces and soil biomes were the potential source environments of the surface microbiomes. Neutral model prediction suggested that microbial community assembly was significantly driven by stochastic processes. Co-association patterns varied with sampling zones and waste types, and neutral amplicon sequence variants (ASVs) that fall within the 95 % confidence intervals of neutral model were largely involved in the stability of microbial networks. These findings improve our understanding of the distribution pattern and the underlying assembly of microbial community on the dustbin surface, thus enabling prospective prediction and assessment of urban microbiomes and their impacts on human health.
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