Literature DB >> 35699790

Characteristics of the microbiota and metabolic profile of high-temperature Daqu with different grades.

Yuandi Zhang1, Fang Ding1, Yi Shen2, Wei Cheng2, Yansong Xue1, Bei-Zhong Han1, Xiaoxue Chen3.   

Abstract

The superior grade Daqu (S_Daqu) and normal grade Daqu (N_Daqu) have obvious differences in flavor, fracture surface, appearance, etc., which can be accurately grouped by well-trained panel based on their sensory properties. However, the differences in microbial community diversity and metabolites between the S_Daqu and N_Daqu were still unclear. The culture-dependent method, the third generation Pacific Biosciences (PacBio) single-molecule, real-time (SMRT) sequencing technology, and nuclear magnetic resonance (NMR) were combined to show the characteristics in microorganisms and metabolites. Results showed that the fungal counts were higher in N_Daqu while the richness of bacterial communities was higher in S_Daqu (P < 0.05). Lentibacillus, Burkholderia, Saccharopolyspora, Thermoascus, and Rasamsonia were the dominant genera of S_Daqu while Staphylococcus, Scopulibacillus, and Chromocleista were the dominant genera in N_Daqu. The content of differential acids, amino acids, and alcohols including fumarate, glucuronate, glycine, 4-carboxyglutamate, and myo-inositol in S_Daqu was higher than that in N_Daqu by 1H NMR coupled with multivariate statistical analysis. The network analysis regarding microbes and metabolites suggested that Saccharopolyspora showed a strong positive correlation with 4-carboxyglutamate while Thermoascus and Chromocleista were highly negatively correlated with alanine and isobutyrate, respectively. Linear Discriminant Analysis (LDA) Effect Size (LEfSe) revealed that Macrococcus and Caulobacter were regarded as bacterial biomarkers in the S_Daqu while Chromocleista was the key fungal genera in N_Daqu. Functionality prediction indicated that the bacteria in S_Daqu were largely involved in more metabolic activities including biosynthesis, degradation, detoxification, and generation of precursor metabolite and energy.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  Daqu; Incubation; Metabolites; Microbiota; PacBio

Mesh:

Year:  2022        PMID: 35699790     DOI: 10.1007/s11274-022-03303-7

Source DB:  PubMed          Journal:  World J Microbiol Biotechnol        ISSN: 0959-3993            Impact factor:   3.312


  6 in total

1.  Effects of initial temperature on microbial community succession rate and volatile flavors during Baijiu fermentation process.

Authors:  Hongxia Zhang; Li Wang; Heyu Wang; Fan Yang; Liangqiang Chen; Fei Hao; Xibin Lv; Hai Du; Yan Xu
Journal:  Food Res Int       Date:  2020-11-10       Impact factor: 6.475

2.  Exploring the diversity and role of microbiota during material pretreatment of light-flavor Baijiu.

Authors:  Xiao-Na Pang; Xiao-Ning Huang; Jing-Yu Chen; Hui-Xin Yu; Xiao-Yong Wang; Bei-Zhong Han
Journal:  Food Microbiol       Date:  2020-04-19       Impact factor: 5.516

3.  Metabolomic profiles of the liquid state fermentation in co-culture of A. oryzae and Z. rouxii.

Authors:  Zeping Liu; Bo Kang; Xinrui Duan; Yong Hu; Wei Li; Chao Wang; Dongsheng Li; Ning Xu
Journal:  Food Microbiol       Date:  2021-12-08       Impact factor: 5.516

4.  Characterization of bacteria and yeasts isolated from traditional fermentation starter (Fen-Daqu) through a 1H NMR-based metabolomics approach.

Authors:  Rui-Yao Li; Xiao-Wei Zheng; Xin Zhang; Zheng Yan; Xiao-Yong Wang; Bei-Zhong Han
Journal:  Food Microbiol       Date:  2018-03-30       Impact factor: 5.516

5.  Analysis of microbial diversity and functional differences in different types of high-temperature Daqu.

Authors:  Yurong Wang; Wenchao Cai; Wenping Wang; Na Shu; Zhendong Zhang; Qiangchuan Hou; Chunhui Shan; Zhuang Guo
Journal:  Food Sci Nutr       Date:  2020-12-17       Impact factor: 2.863

6.  Optimization of lipase production by Burkholderia sp. using response surface methodology.

Authors:  Chia-Feng Lo; Chi-Yang Yu; I-Ching Kuan; Shiow-Ling Lee
Journal:  Int J Mol Sci       Date:  2012-11-13       Impact factor: 5.923

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.