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Updated: Sep 21, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
Spatial heterogeneity of the microbiome and metabolome profiles of high-temperature Daqu in the same workshop
Wei Shi1, Li-Juan Chai2, Guan-Yu Fang3
1Key Laboratory of Industrial Biotechnology of Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi 214122, PR China; National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University, Wuxi 214122, PR China; Department of Brewing Engineering, Moutai Institute, Renhuai 564507, PR China.
Abstract:
High-temperature Daqu, usually used as a fermentation starter for sauce-flavor Baijiu production, plays an essential role in the yield and flavor quality of Baijiu. The environmental heterogeneity of different locations in the workshop during fermentation led to the final production of Daqu with three different types (i.e., white, yellow, and black Daqu). How to use these three types of Daqu in Baijiu production mainly depends on the workers' experience so far. Here, we aimed to reveal the potential functions of different types of Daqu by comparing enzyme activity, volatile metabolites, and microbiota characteristics. White_Qu exhibited the highest liquefaction and saccharification enzyme activities, while the highest neutral proteinase and cellulase enzyme activities were detected in black_Qu. The total volatile content of yellow_Qu and black_Qu was roughly double that of white_Qu, and multivariate analysis revealed distinct volatile dissimilarities across different types of Daqu. Significant differences in bacterial and fungal community structures, assembly patterns, and potential functional profiles were discovered among different types of Daqu. At the genus level, Oceanobacillus and Thermomyces dominated the white_Qu microbiota, and the abundant microbes in yellow_Qu and black_Qu were scattered in Kroppenstedtia and Thermoascus. Bacterial and fungal communities were dominated by deterministic and stochastic assembly processes, respectively, suggesting that bacteria may be more affected by abiotic environmental factors and species interaction than fungi. Co-occurrence network analysis showed positive correlations characterized Daqu microbial networks, and network topological features indicated stronger interactions between bacterial taxa compared with fungal community. The Spearman correlation analysis revealed that four bacterial genera (Kroppenstedtia, Virgibacillus, Scopulibacillus, and Staphylococcus) and two fungal genera (Thermoascus and Aspergillus) exhibited positive correlations with almost all of the abundant volatiles. This work reveals that spatially varying environments lead to the microbiome and metabolome heterogeneity of high-temperature Daqu in the same workshop.
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