评估发酵食品微生物群中的酶多样性
Peng Li1, Jingyu Sun1, Yu Geng1
1State Key Laboratory of Microbial Technology, Institute of Microbial Technology, Shandong University, Qingdao 266237, China.
Cell systems
|November 5, 2025
概括
这项研究使用机器学习揭示了发酵食品中大量尚未探索的酶多样性. 这些微生物酶提供了对食品质量和安全至关重要的新功能.
科学领域:
- 微生物学 微生物学
- 生物技术是生物技术.
- 生物信息学是一种生物信息学.
背景情况:
- 微生物酶对于发酵食品的特性至关重要,包括味道,外观,质量和安全性.
- 酵素资源的全部范围及其在发酵食品生态系统中的分布尚不清楚.
研究的目的:
- 探索和描述全球发酵食品中的酶多样性.
- 识别新的酶功能,了解它们的分布和适应性.
- 开发一个预测模型,以基于酶特征来对发酵食品来源进行分类.
主要方法:
- 分析了来自各种发酵食品的10202个元基因组组装基因组.
- 机器学习的应用用于酶识别,聚类和功能注释.
- 预测酶特性,如最佳温度,pH值和利基范围.
主要成果:
- 识别了超过500万个酶序列,在3000多种酶类型中形成了98,693个同源集群.
- 发现84.4%的已识别的酶缺乏当前的数据库注释,特别是在类和多基类代谢中.
- 酸酸酶表现出广泛的适应性,31.3%的酶集群对特定的食物类型表现出特异性.
- 开发一种能够通过酶集群对发酵食品来源进行分类的机器学习模型.
结论:
- 发酵食品环境具有重要的,尚未开发的酶潜力.
- 发现的新型酶对提高食品质量,安全性和研究有影响.
- 了解酶的分布和功能提供了对微生物在食品发酵中的作用的关键见解.
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