ArticleJournal of advanced research2026
Metabolic interactions drive microbial community succession and functional expression of Nongxiangxing (Strong-flavor) daqu.
Article in Journal of advanced research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Multi-omics analysis reveals the aging mechanism during Baobaoqu storage for the production of Wuliangye Baijiu.Food chemistry: X · 2026Article
- Genome-Scale Metabolic Models Guided Improvement of Fermented Milk Quality and Flavor byFoods (Basel, Switzerland) · 2026Article
- A High Esterifying Enzyme-ProducingFoods (Basel, Switzerland) · 2026Article
- A Paradigm Shift in Microbial Protein Manufacturing.Life (Basel, Switzerland) · 2026Review
- Multi-Omics Insights into Microbial Community Dynamics and Functional Shifts During Double-Round Bottom Fermentation of Strong-Flavor Baijiu.Foods (Basel, Switzerland) · 2025Article
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9 authors.
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Abstract
introductionNongxiangxing daqu is a wheat-based fermentation starter used in the production of Baijiu (a traditional Chinese distilled spirit), whose fermentation process during storage directly affects its quality. However, the dynamics of microbial succession and metabolism during daqu storage, particularly the functional contributions of specific microorganisms to enzyme formation and their metabolic interactions, remain unclear.
objectivesThis study aimed to investigate the temporal dynamics of microbial community structure, function, and enzymatic activity in daqu during storage, with a focus on metabolic interactions such as cross-feeding and metabolic division of labor (MDOL).
methodsMetagenomic and metaproteomic analyses were integrated to profile microbial taxa, functional genes, and protein expression across storage time points. Weighted gene co-expression network analysis (WGCNA) linked gene modules to storage time. Genome-scale metabolic models (GEMs) were constructed to infer metabolic interaction networks among microbes.
resultsPaecilomyces variotii, Rasamsonia emersonii, Rhizopus microsporus, Rhizopus delemar, Kroppenstedtia eburnea, and Weissella confusa were dominant species. In total, 14,588 protein groups were identified, including 6,801 enzymes enriched in carbohydrate, amino acid, and energy metabolism. Glucosidase activity was primarily attributed to Rasamsonia, Thermoascus, Aspergillus, Thermomyces, and Paecilomyces. Functional genes and enzymes declined sharply after month 1, reached a nadir at month 3, and partially rebounded by month 4. WGCNA identified 16 gene modules associated with storage (maximum r = 0.97, P < 0.01). Cross-feeding patterns were identified among Weissella confusa, Kroppenstedtia eburnea, Saccharopolyspora rectivirgula, and Enterobacteriaceae. The MDOL model revealed cooperative metabolic roles among Actinomycetota, Bacillota, Ascomycota, and Mucoromycota in converting raw materials into flavor compounds.
conclusionThese findings improve the understanding of microecological dynamics during daqu storage and provide a theoretical basis for regulating and optimizing the fermentation process during the storage period.
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