Literature DB >> 29579944

Characterization of microbial community structure and metabolic potential using Illumina MiSeq platform during the black garlic processing.

Zhichang Qiu1, Ningyang Li1, Xiaoming Lu1, Zhenjia Zheng1, Mingjie Zhang1, Xuguang Qiao2.   

Abstract

Black garlic is a distinctive garlic deep-processed product made from fresh garlic at high temperature and controlled humidity. To explore microbial community structure, diversity and metabolic potential during the 12days of the black garlic processing, Illumina MiSeq sequencing technology was performed to sequence the 16S rRNA V3-V4 hypervariable region of bacteria. A total of 677,917 high quality reads were yielded with an average read length of 416bp. Operational taxonomic units (OTU) clustering analysis showed that the number of species OTUs ranged from 148 to 1974, with alpha diversity increasing remarkably, indicating the high microbial community abundance and diversity. Taxonomic analysis indicated that bacterial community was classified into 45 phyla and 1125 distinct genera, and the microbiome of black garlic samples based on phylogenetic analysis was dominated by distinct populations of four genera: Thermus, Corynebacterium, Streptococcus and Brevundimonas. The metabolic pathways were predicted for 16S rRNA marker gene sequences based on Kyoto Encyclopedia of Genes and Genomes (KEGG), indicating that amino acid metabolism, carbohydrate metabolism and membrane transport were important for the black garlic fermentation process. Overall, the study was the first to reveal microbial community structure and speculate the composition of functional genes in black garlic samples. The results contributed to further analysis of the interaction between microbial community and black garlic components at different stages, which was of great significance to study the formation mechanism and quality improvement of black garlic in the future.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Black garlic; High-throughput sequencing; Metabolic potential; Metagenome; Microbial diversity

Mesh:

Year:  2018        PMID: 29579944     DOI: 10.1016/j.foodres.2017.12.081

Source DB:  PubMed          Journal:  Food Res Int        ISSN: 0963-9969            Impact factor:   6.475


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