ABSTRACT: Xiaoqu, one of three traditional jiuqu in China, is a saccharifying and fermenting agent used in Xiaoqu jiu brewing, with different ingredient compositions and preparation techniques used in various regions. The yield and quality of Xiaoqu jiu are significantly affected by the metabolites and microbiota of Xiaoqu; however, the associated relationship remains poorly understood. This study aimed to analyze this relationship in three typical traditional Xiaoqu from the Guizhou province in China. The non-volatile metabolites of Xiaoqu were detected using gas chromatography time-of-flight mass spectrometry, whereas the classification and metabolic potential of the microbiota were investigated using metagenomic sequencing. Results show that Firmicutes, Proteobacteria, and Actinobacteria represent the dominant bacterial phyla, with Lactobacillus, Bacillus, Acinetobacter, Leuconostoc, and Weissella found to be the dominant bacterial genera. Meanwhile, Ascomycota, Mucoromycota, and Basidiomycota are the dominant fungal phyla with Aspergillus, Saccharomyces, Pichia, Rhizopus, and Phycomyces being the predominant fungal genera. Functional annotation of the microbiota revealed a major association with metabolism of carbohydrates, cofactors, and vitamins, as well as amino acids. A total of 39 significantly different metabolites (SDMs) were identified that are involved in 47 metabolic pathways, primarily that of starch and sucrose; glycine, serine, and threonine; glyoxylate and dicarboxylate; pyruvate; as well as biosynthesis of pantothenate and CoA. Further, based on Spearman's correlation analysis, Aspergillus, Saccharomyces, Lactobacillus, Acetobacter, Weissella, Pantoea, Desmospora, and Bacillus are closely correlated with production of physicochemical indexes and SDMs. Moreover, the metabolic network generated for the breakdown of substrates and formation of SDMs in Xiaoqu was found to primarily center on the metabolism of carbohydrates and the tricarboxylic acid cycle. These results provide insights into the functional microorganisms and metabolic patterns present in traditional Guizhou Xiaoqu and might guide researchers in the production of stable and efficient Xiaoqu in the future.
