Integrating multi-omics to link core and region-specific microbiota to flavor metabolism in medium-temperature Daqu

Medium-temperature Daqu (MTD) is a critical fermentation starter for strong-aroma Baijiu, where its complex microbiota governs flavor development. We combined metagenomics with GC-MS metabolomics to analyze 15 MTD samples from six major producing regions in China, moving from descriptive profiling to mechanistic insight. Although microbial communities exhibited substantial regional variation, a conserved core microbiota emerged, consisting of eight fungal genera, including Aspergillus and Rhizopus, and five bacterial genera such as Bacillus. Beta diversity analysis indicated that producer-specific practices were more influential than geography in structuring these communities. Functional metagenomic profiling showed enriched pathways for carbohydrate, amino acid, and ester metabolism. Volatile metabolite analysis identified 94 compounds, primarily esters, with 12 common to all samples. We constructed multi-omics correlation networks to predict functional linkages, which notably connected genera like Talaromyces and Aspergillus to key flavor esters. Based on these predictions, we isolated Wickerhamomyces anomalus and Bacillus velezensis from Daqu. In vitro validation demonstrated their functional roles: W. anomalus produced ethyl acetate, while co-culturing B. velezensis with Saccharomyces cerevisiae significantly enhanced the yield of ethyl decanoate and ethyl laurate. This work delineates both the core and region-specific metabolic features of MTD and translates multi-omics correlations into confirmed microbial activities. It thereby establishes a targeted framework for identifying flavor-active microorganisms, offering a scientific foundation for quality control and directed bioaugmentation in Daqu production.