TY - JOUR
AU1 - Wang, Fan
AU2 - Zhao, Hongwei
AU3 - Xiang, Haiying
AU4 - Wu, Lijun
AU5 - Men, Xiao
AU6 - Qi, Chang
AU7 - Chen, Guoqiang
AU8 - Zhang, Haibo
AU9 - Wang, Yi
AU1 - Xian, Mo
AB - Microbes on aging flue-cured tobaccos (ATFs) improve the aroma and other qualities desirable in products. Understanding the relevant organisms would picture microbial community diversity, metabolic potential, and their applications. However, limited efforts have been made on characterizing the microbial quality and functional profiling. Herein, we present our investigation of the bacterial diversity and predicted potential genetic capability of the bacteria from two AFTs using 16S rRNA gene sequences and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) software. The results show that dominant bacteria from AFT surfaces were classified into 48 genera, 36 families, and 7 phyla. In addition, Bacillus spp. was found prevalent on both ATFs. Furthermore, PICRUSt predictions of bacterial community functions revealed many attractive metabolic capacities in the AFT microbiota, including several involved in the biosynthesis of flavors and fragrances and the degradation of harmful compounds, such as nicotine and nitrite. These results provide insights into the importance of AFT bacteria in determining product qualities and indicate specific microbial species with predicted enzymatic capabilities for the production of high-efficiency flavors, the degradation of undesirable compounds, and the provision of nicotine and nitrite tolerance which suggest fruitful areas of investigation into the manipulation of AFT microbiota for AFT and other product improvements.
TI - Species Diversity and Functional Prediction of Surface Bacterial Communities on Aging Flue-Cured Tobaccos
JF - Current Microbiology
DO - 10.1007/s00284-018-1525-x
DA - 2018-06-05
UR - https://www.deepdyve.com/lp/springer-journals/species-diversity-and-functional-prediction-of-surface-bacterial-6rpdzjR0r0
SP - 1306
EP - 1315
VL - 75
IS - 10
DP - DeepDyve
ER -