在Pichia pastoris中深度学习驱动的酶工程:高产量的Nootkatone生物合成的可持续平台
Hui Li1, Yichen Yang1, Shuting Hou1
1State Key of Bioreactor Engineering, New World Institute of Biotechnology, East China University of Science and Technology, Shanghai, China.
BioFactors (Oxford, England)
|October 14, 2025
概括
这项研究利用代谢工程和人工智能引导的酶设计,为更高的nootkatone生产设计了酵母. 优化的菌株实现了3365.36毫克/升的创纪录产量,提供了可持续的生物基生产方法.
科学领域:
- 生物技术是生物技术.
- 代谢工程是代谢工程.
- 合成生物学 合成生物学
背景情况:
- 诺卡是一种有价值的甲,具有多种应用.
- 诺卡的微生物合成受到代谢和酶效率低下的限制.
研究的目的:
- 通过结合代谢工程和深度学习方法,增强Pichia pastoris中的nootkatone产量.
- 为Nootkatone生物合成开发一个可持续和高效的微生物平台.
主要方法:
- 在Pichia pastoris中,梅瓦酸路径和辅因子供应的代谢工程.
- 使用祖先序列重建 (ASR) 和DLKcat.使用cytochrome P450 (HPO) 的深度学习引导的酶工程.
- 优化发酵策略,包括间歇性养.
主要成果:
- 开发了一种酵母菌株,产生702.15mg/L的烯.
- 设计了一种HPO变种 (H54A),具有2.3倍高的催化性能.
- 通过优化发酵实现了3365.36 mg/L的诺卡纪录产量.
结论:
- 该研究提出了一个高效,可持续的生物基生产平台,用于nootkatone.
- 展示了整合人工智能和代谢工程以优化生物活性化合物生物合成的潜力.
- 提供了一种可扩展的方法来生产高价值的类.
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