Contrasting the microbial community and metabolic profile of three types of light-flavor Daqu

韦斯拉 乳酸菌 食品科学 片球菌 生物 发酵 短乳杆菌 醋酸杆菌 乳杆菌科 代谢组学 植物乳杆菌 乳酸 丙酸杆菌 细菌 生物化学 明串珠菌 生物信息学 遗传学
作者
Yunan Hu,Xiaoning Huang,Bo Yang,Xin Zhang,Ying Han,Xiaoxue Chen,Bei‐Zhong Han
出处
期刊:Food bioscience [Elsevier]
卷期号:44: 101395-101395 被引量:53
标识
DOI:10.1016/j.fbio.2021.101395
摘要

Light-flavor Baijiu often obtained using mixed Daqu - Houhuo (HH), Hongxin (HX), and Qingcha (QC) as starter culture for fermentation. These three types of low-temperature Daqu were incubated by traditional manual temperature control procedures. However, differences in their microbial communities and metabolite profiles remain largely unknown. Herein, microbial communities and metabolites in the three types of Daqu were compared using high-throughput sequencing and nuclear magnetic resonance analyses. Furthermore, the correlation between microbes and metabolites was constructed. Lactobacillus, Weissella were the dominant bacteria, whereas Pichia and Saccharomycopsis were the dominant fungi in all the three types of Daqu. The abundance of Lactobacillus was highest in HH (72.56%) and Weissella was highest in QC (32.62%). The abundance of Pichia was similar among three types of Daqu, while Saccharomycopsis and Lichtheimia showed the highest abundance in QC individually. Linear Discriminant Analysis (LDA) Effect Size (LEfSe) revealed that Lactobacillus, Acetobacter, and Bacillus were the main biomarkers in the three types of Daqu. Ethanol, glucose, proline, and lactate were identified as the most abundant metabolites. Furthermore, the metabolic functions of microbes were predicted, and amino acid metabolism, energy metabolism, and lipid metabolism were identified as the major metabolic pathways in Daqu. Correlation analysis indicated that lactate and acetate were negatively correlated with Lactobacillus, Acetobacter, and Bacillus. Antimicrobial compounds (i.e., betaine and choline) were negatively correlated with Brachybacterium, Corynebacterium, and Brevibacterium. The results shed light on the manual temperature control techniques for Daqu microbiome formation and provide new insights into managing the traditional fermentation process.
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