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Dynamic characteristics and co-occurrence patterns of microbial community in tobacco leaves during the 24-month aging process

放线菌门 蛋白质细菌 生物 拟杆菌 厚壁菌 微生物种群生物学 微生物生态学 子囊菌纲 物种丰富度 植物 相对物种丰度 多样性指数 微生物群 16S核糖体RNA 微生物 食品科学 丰度(生态学) 生态学 细菌 基因 生物信息学 生物化学 遗传学
作者
Jiaxi Zhou,Lifei Yu,Jian Zhang,Jing Liu,Xiao Zhou
出处
期刊:Annals of Microbiology [Springer Nature]
卷期号:71 (1) 被引量:18
标识
DOI:10.1186/s13213-021-01620-0
摘要

Abstract Purpose Microorganisms are important in tobacco aging. These are used to improve the quality of tobacco leaves after threshing and redrying. However, the response of microbial community to the storage environment and time during the tobacco aging process has been less explored. This study aimed to characterize the dynamic changes in microbial community composition and diversity in tobacco leaf samples. Methods In this study, 16S and ITS rRNA gene amplicon sequencing techniques were used to characterize the composition, diversity, and co-occurrence of the microbial community in tobacco leaves stored in two different cities during the 24-month aging. Furthermore, the activities of several enzymes were measured spectrophotometrically, and the correlation between the microbiota and enzyme activity was analyzed by network analysis. Results Shannon diversity and Chao richness of bacterial communities gradually increased during the first 18 months, whereas those of the fungal community decreased. The relative abundance of Proteobacteria decreased, whereas that of Actinobacteria and Bacteroidetes increased. The proportion of Ascomycota gradually increased during the first 18 months and then rapidly decreased, whereas the proportion of Basidiomycota exhibited a completely opposite pattern. The change in the composition of bacterial community and dominant genera in leaves was not significant between Guiyang city and Maotai city storerooms, but that in the fungal community was significant. The network analysis revealed that fungal networks were more complex and compact than bacterial networks, and a strong negative correlation existed between bacteria and fungi. Moreover, the bacterial microbiome showed a strong positive association with amylase activity, while the fungal microbiome positively correlated with cellulase activity. Conclusions This study demonstrated a significant spatiotemporal heterogeneity in the composition of the microbial community during tobacco aging and highlighted the possible influence of the interactions and enzyme activity on microbial diversity and composition. The findings provided a scientific basis for using microorganisms to regulate and control tobacco aging.
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