The diversity, structure and function of microbial communities changes across aging process of tobacco leaves

ENVIRONMENTAL RESEARCH COMMUNICATIONS(2022)

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摘要
Microbial communities that inhabit aging tobacco leaves play a key role in improving products quality. A better understanding of microbial communities on the aging of tobacco leaves could provide an important microbial repository for the industrial applications. Here, we examined the structural and compositional changes of microbial communities throughout the aging process of by tobacco leaves 16 S and ITS rRNA amplicon sequencing techniques and identified the potential metabolic pathways of bacteria and fungi using Functional Annotation of Prokaryotic Taxa (FAPROTAX) and Fungi Functional Guild (FUNGuild), respectively. The results showed that the diversity and structure of the microbial communities keep changing along with the aging process went on. The richness and diversity of bacterial community decreased, while the richness of fungal community was in an inverse trend. At the phylum level, the bacterial community was dominated by Proteobacteria, Actinobacteria, and Firmicutes, while Ascomycota and Basidiomycota were the dominant species in the fungal community. In the bacterial community, metabolic functions related to the carbon and nitrogen cycles which response to the degradation of harmful components, and the metabolism of aromatic hydrocarbons showed extremely dynamic at different aging periods. The change of the main nutritional mode of the fungal community also led to an increase in the abundance of saprophytic fungi. These results provide information on the succession of microbial community structure and function in the whole process of tobacco aging and suggest that the aging process of tobacco leaves can be a natural microbial collection for target microorganism and their metabolites. It also enables the further investigation of coordination mechanisms between beneficial microbial regulation and pathogenicity during aging process.
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关键词
tobacco leaves, aging, microbial diversity, community structure, function prediction
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