Selection of initial microbial community for the alcoholic fermentation of sesame flavor-type baijiu.

The initial microbial community is critical for the production of volatile metabolites during traditional food fermentations. Selection of the initial community plays an important role in improving the quality of fermented foods. Here, we used high-throughput amplicon sequencing combined with multivariate statistical methods to explore the microbial succession in stacking and alcoholic fermentation stages in sesame flavor-type baijiu making. We proposed a selection strategy for the initial microbial community in the alcoholic fermentation stage, which determined the quality of baijiu. Results suggested that the microbial composition statistically differed between stacking and alcoholic fermentation stages (ANOSIM, Bacteria: R = 0.60, P = 0.001; Fungi: R = 0.53, P = 0.001). Microbial succession drove metabolic succession (Bacteria: r = 0.87, P < 0.05; Fungi: r = 0.56, P < 0.05) in alcoholic fermentation. The fermentation time of stacking fermentation determined the initial community for alcoholic fermentation, and it can be used as a criterion for selection of the initial microbial community for alcoholic fermentation. The succession distance of the microbial community was varied and reached the highest (Bacteria: 0.048, Fungi: 0.064) at 30 h in stacking fermentation. When we selected 30 h as stacking fermentation time, the concentration (4.58 mg/kg) and diversity (0.61) of volatile metabolites were highest at the end of alcoholic fermentation. This work developed a succession distance-guided approach to select the initial microbial community for the alcoholic fermentation of sesame flavor-type baijiu. This approach can be used to improve the quality of baijiu.

Acidity drives volatile metabolites in the spontaneous fermentation of sesame flavor-type baijiu.

Environmental factors play an important role in contributing to intricate compositional dynamics and volatile metabolites in food fermentation. However, our understanding of which and how environmental factors affect volatile metabolites during sesame flavor-type baijiu fermentation is poor. Here, we examined the effects of environmental factors on the bacterial and fungal community to determine how changes in representative factors impact the microbial structure, diversity, and volatile metabolites in three fermentations. Results showed that bacterial community (ANOSIM: R = 0.79, P = 0.001), fungal community (ANOSIM: R = 0.65, P = 0.001), and volatile metabolites (ANOSIM: R = 0.84, P = 0.001) were significantly different in three fermentations. Acidity, ethanol, and moisture negatively impacted bacterial composition and diversity (P < 0.05). The fungal diversity and structure were positively and significantly affected by acidity (path coefficient, b = 0.54 for diversity, b = 0.35 for structure, P < 0.05). The fungal community rather than the bacterial community was the strongest driver of volatile metabolites. Fungal structure and diversity were equally important for the composition and content of volatile metabolites (structure: b = 0.50, diversity: b = 0.56, P < 0.05). 66 % of variations in volatile metabolites could be explained. Altogether these results indicated that acidity strongly drove volatile metabolites by modulating fungal structure and diversity. This work provides insights into managing volatile metabolites by regulating initial acidity in sesame flavor-type baijiu fermentation.

Initial fungal diversity impacts flavor compounds formation in the spontaneous fermentation of Chinese liquor.

Microbiota plays an important role in flavor compounds formation during food fermentation. However, the role of initial microbial diversity in regulating flavor compounds formation is still unclear. Here, we used high-throughput amplicon sequencing and structural equation modeling to reveal the effect of initial microbial diversity on final metabolic diversity in Chinese sesame flavor-type liquor fermentation. The results showed that the initial fungal diversity positively impacted fungal succession (R = 0.74, P < 0.001). The longest fungal succession distance (0.054) was observed at the highest initial fungal diversity (38.580). Moreover, fungal succession positively affected metabolic succession (R = 0.71, P < 0.001), and the metabolic succession positively promoted the metabolic diversity (R = 0.68, P < 0.001). In addition, the longest succession distance of fungi (0.054) led to the longest succession distance of metabolites (0.065), and resulted in the highest metabolic diversity (0.409), that was significantly higher than the lowest metabolic diversity (0.219) (P < 0.05). Finally, a simulative fermentation experiment verified the significant and positive effect of initial fungal diversity on final metabolic diversity (R2 = 0.52, P < 0.05) in liquor fermentation. These results indicated the importance of initial fungal diversity for promoting flavor compounds formation. This work provides insights into improving flavor compounds formation by controlling initial fungal diversity in food fermentation, and it will be beneficial for improving the quality of fermented foods.

Sugar profile regulates the microbial metabolic diversity in Chinese Baijiu fermentation.

Cereals are widely used as raw material for food fermentation, and they can provide a variety of sugars in the fermentation via saccharification. However, the effect of sugar profile on microbial metabolism in spontaneous food fermentation is still unclear. Here, this work studied the regulation of sugar profile on the diversity of microbiota and their metabolism in Chinese Baijiu fermentation using sorghum as raw material. Six sugars were detected during Baijiu fermentation with 6 different cultivars of sorghum. The diversity of microbiota (ANOSIM: bacteria: P = 0.001, R = 0.77; fungi: P = 0.009, R = 0.33) and metabolites (ANOSIM: P = 0.001, R = 0.50) had different profiles during Baijiu fermentation. Among these sugars, glucose, fructose, and arabinose were identified as key sugars driving both the microbial and the metabolic diversity during Chinese Baijiu fermentation, and the metabolic diversity was positively correlated with the microbial diversity (P < 0.05). Hence, response surface methodology was used to establish a predictive model for regulating the metabolic diversity with the combination of three key sugars. The metabolic diversity significantly increased to 0.42 with the optimized levels of glucose (31.82 g/L), fructose (4.81 g/L), and arabinose (0.20 g/L), compared with unoptimized low-level average metabolic diversity (0.29). This work would provide a strategy to control microbial metabolism in spontaneous food fermentation, hence to improve the quality of fermented foods.

Construction of a synthetic microbial community for the biosynthesis of volatile sulfur compound by multi-module division of labor.

3-(Methylthio)-1-propanol, reminiscent of cauliflower and cooked vegetable aroma, is an important sulfur compound in Baijiu. It is important to develop a method to increase 3-(methylthio)-1-propanol content to improve flavor quality of products. In this study, a synthetic microbial community was employed to enhance the content of 3-(methylthio)-1-propanol by multi-module division of labor approach. Firstly, the synthetic pathway of 3-(methylthio)-1-propanol was reconstructed and classified into three modules. Later, the hyper producers in each module were isolated and negative interaction between the members was relieved. Finally, a synthetic microbial community was constructed using three species containing one hyper producer from each module. Furthermore, the transcription characteristics of the species in each module were validated by metatranscriptomic analysis. The constructed synthetic microbial community can be used to biosynthesize 3-(methylthio)-1-propanol for Baijiu. This work provided a novel and workable strategy to design synthetic microbial community to enhance the flavor feature of other fermented foods.

Selection of non-Saccharomyces yeasts for orange wine fermentation based on their enological traits and volatile compounds formation.

In order to select the non-Saccharomyces yeasts for orange wine fermentation, the enological traits and volatile compounds formation of ten non-Saccharomyces yeast strains were evaluated through physicochemical methods and solid-phase microextraction coupled to GC-MS, respectively. The results indicated that non-Saccharomyces yeast fermentation had lower maximum populations (7.8-8.0 Log cfu/mL), longer fermentation period (7-10 days), lower ethanol (4.13-7.79%), lower total acids (7.48-8.51 g/L) and higher volatile acids concentrations (0.08-0.23 g/L) when compared with those of Saccharomyces cerevisiae fermentation. Hanseniaspora uvarum, Hanseniaspora opuntiae, Hanseniaspora occidentalis, Pichia kudriavzevii and Torulaspora delbrueckii were selected as candidates for orange wine fermentation with higher volatile compounds concentration, odor active values and sensory evaluation scores. This study will provide a valuable selection method of non-Saccharomyces yeasts for orange wine fermentation, and an approach to improve the flavor of orange wine or other fruit wine.