机器学习模型的催化效率和基质特异性的acyl-ACP thioesterase变体产生的自然和体外导向进化
Fuyuan Jing1,2,3, Keting Chen1,4, Marna D Yandeau-Nelson2,3,4
1Roy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, IA, United States.
Frontiers in bioengineering and biotechnology
|April 26, 2024
概括
研究人员通过进化acyl-ACP thioesterase (TE) 酶,改善了大肠杆菌中的脂肪酸生产. 定向进化产生了新的TE变体,脂肪酸产量高达10倍,以及改变的配置文件.
科学领域:
- 生物技术是生物技术.
- 合成生物学 合成生物学
- 酶工程是什么? 酶工程是什么?
背景情况:
- 乙-ACP化酶 (TE) 活性对于脂肪酸生物合成至关重要.
- 调节TE是增强脂肪酸生产和多样性的关键目标.
研究的目的:
- 开发一种有针对性的进化方法,以改善乙-ACP化酶 (TE),以增加脂肪酸标位和多样性.
- 确定影响TE催化效率和基质特异性的关键氨基酸残留物.
主要方法:
- 采用单一一轮的体外定向进化与高通量查相结合.
- 利用随机森林分类器机器学习模型来分析变体TEs.
主要成果:
- 鉴定出26种新型的乙-ACP TE变体,脂肪酸标位增加了10倍.
- 在表达变异TE的大肠杆菌菌株中观察到改变的脂肪酸概况.
- 一个机器学习模型确定了22个影响TE功能的关键氨基酸残留物.
结论:
- 定向进化对于生成改进的乙-ACP TE 变体是有效的.
- 了解关键残留物可以指导未来的脂肪酸生物合成的酶工程.
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