4.7 Article

Sugar profile regulates the microbial metabolic diversity in Chinese Baijiu fermentation

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Publisher

ELSEVIER
DOI: 10.1016/j.ijfoodmicro.2021.109426

Keywords

Food fermentation; Sorghum; Microbial diversity; Regulation

Funding

  1. National Natural Science Foundation of China (NSFC) [31530055]
  2. National Key R&D Program of China [2018YFD0400402]
  3. Priority Academic Program Development of Jiangsu Higher Education Institutions
  4. 111 Project [111-2-06]
  5. Collaborative Innovation Center of Jiangsu Modern Industrial Fermentation
  6. National First-Class Discipline Program of Light Industry Technology and Engineering [LITE2018-12]

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This study investigated the regulation of sugar profile on microbial diversity and metabolism in Chinese Baijiu fermentation using sorghum as raw material. Glucose, fructose, and arabinose were identified as key sugars driving microbial and metabolic diversity during fermentation. The metabolic diversity significantly increased with optimized levels of these sugars, providing a strategy to control microbial metabolism and improve the quality of fermented foods.
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.

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