在合成大豆糊中揭示微生物相互作用 微生物社区
Chunfeng Liu1, Feng Yi1, Chengtuo Niu1
1Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122, China; Lab of Brewing Science and Technology, School of Biotechnology, Jiangnan University, Wuxi, 214122, China.
Food microbiology
|April 10, 2025
概括
这项研究利用合成社区和一般化的Lotka-Volterra模型绘制了广泛豆发酵中的微生物相互作用. 一个有针对性的注射策略显著改善了面糊的风味和香味特征.
科学领域:
- 食品微生物学 食品微生物学
- 发酵科学 发酵科学
- 微生物生态学 微生物生态学
背景情况:
- 大豆发酵的微生物生态是复杂的,并没有被充分理解.
- 识别关键的微生物相互作用对于优化发酵和风味发展至关重要.
研究的目的:
- 构建和分析用于广泛豆发酵的合成微生物群体.
- 使用一般化的Lotka-Volterra (gLV) 模型阐明关键微生物之间的相互作用网络.
- 应用交互网络的洞察力来增强宽豆的发酵.
主要方法:
- 构建一个合成社区,其中包括六种主要物种:Zygosaccharomyces rouxii,Staphylococcus carnosus,Bacillus subtilis,Bacillus amyloliquefaciens,Tetragenococcus halophilus和Weissella confusa.
- 应用广义的Lotka-Volterra (gLV) 模型来预测微生物的丰富性和分析相互作用网络.
- 基于已识别的微生物相互作用,开发顺序注射策略.
主要成果:
- 该gLV模型准确地预测了多个物种群体中的物种丰度.
- 微生物相互作用主要由双对相互作用主导,负面相互作用比积极相互作用更为普遍 (57%) (37%).
- Zygosaccharomyces rouxii抑制了酸的产生,而Bacillus物种促进了乳酸细菌的生长和积累.
- 优化的顺序注射策略显著增强了和柔和的风味,减少了异味,并增加了挥发性风味化合物的9.43倍.
结论:
- 该gLV模型有效地揭示了大豆中的关键微生物的相互作用网络.
- 了解微生物相互作用对于生物增强策略至关重要.
- 开发的合成社区和注射策略显著改善了大豆糊的风味质量.
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