优化发酵过程的果糖转移酶的生产由黑色阿斯伯吉路斯 FS054 FS054 黑色阿斯伯吉路斯
Yingzi Wu1, Yuewen Zhang1, Xiaoyu Zhong1
1College of Life Sciences, Fujian Normal University, Fuzhou, Fujian, China.
Microbial cell factories
|July 27, 2025
概括
这项研究通过综合实验设计和机器学习优化了使用Aspergillus niger FS054的果糖转酶 (FTase) 生产. 优化过程显著增加了酶活性,为果醇糖 (FOS) 生物合成提供了具有成本效益的来源.
科学领域:
- 生物技术是生物技术.
- 酶工程是什么? 酶工程是什么?
- 工业微生物学 工业微生物学
背景情况:
- 果糖转移酶 (FTase) 对于果糖糖体 (FOS) 生物合成至关重要.
- 优化 FTase 生产对于具有成本效益的工业应用是必不可少的.
- 黑色虫是一种已知的有价值酶的生产者.
研究的目的:
- 系统地优化发酵过程,以提高阿斯伯吉拉斯尼格尔 FS054.05的FTase产量.
- 将传统的实验设计与机器学习相结合,以优化流程.
- 为了实现潜在的工业应用,FTase收益率的显著增加.
主要方法:
- 单因素实验,以确定关键介质组件和种植参数.
- 普莱克特-伯曼选以确定影响媒介因素 (糖糖,酵母提取物糊,NH4Cl).
- 盒子-贝恩肯响应表面方法 (RSM) 用于媒介优化.
- 混合逆向传播神经网络遗传算法 (BP-GA) 用于培养条件优化.
主要成果:
- 最佳介质:糖 156.65 g/L,酵母提取物糊 42 g/L,NH4Cl 1.68 g/L,产生 3249.00 U/L 的 FTase 活性.
- 最佳培养:pH5.5,96.6毫升液体体积,2.4 x 10^4子/毫升注射剂大小.
- 获得了3422.14U/L的最终酶活性,比初始条件增加了4.2倍.
- 预测和实验结果之间的高度一致性 (RSM的99.16%,BP-GA的1.1%偏差).
结论:
- 实验设计和人工智能的协同应用显著提高了FTase的生产力.
- 优化的过程为工业规模的FOS生物合成提供了更经济的酶来源.
- 这项研究为微生物酶生产优化提供了强大的方法.
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