优化多副本染色体的整合,以获得稳定的高性能菌株
1School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing, China.
Nature chemical biology
|June 10, 2024
概括
这项研究引入了一种使用非重复性DNA序列和机器学习的新方法,以优化微生物细胞工厂的基因拷贝数量. 工程菌株显示出增强的生产和遗传稳定性,克服了以前的局限性.
科学领域:
- 合成生物学 合成生物学
- 代谢工程是代谢工程.
- 生物技术是生物技术.
背景情况:
- 微生物细胞工厂的染色体集成可以导致由于重复的DNA序列和同源重组导致遗传不稳定.
- 为代谢途径优化基因拷贝数量是一个复杂的,耗时的过程.
研究的目的:
- 开发一种方法来克服遗传不稳定性,并优化工程微生物菌株中的基因拷贝数量.
- 提高微生物细胞工厂对有价值化合物的生物合成的效率.
主要方法:
- 使用计算器生成多个非重复编码DNA序列 (CDS) 变体.
- 开发一种机器学习模型,以确定最佳的基因拷贝数组合.
- 工程 Yarrowia lipolytica 对于eicosapentaenoic 酸 (EPA) 和埃舍里希亚大肠杆菌用于烯生产.
主要成果:
- 一种经过工程改造的Yarrowia lipolytica菌株在50升生物反应器中实现了27.5g/L EPA的创纪录标位.
- 在工程Escherichia coli中观察到烯生产的显著改善.
- 使用非重复性CDS的所有工程菌株 (Y. lipolytica,E. coli,Saccharomyces cerevisiae) 显示出高遗传稳定性.
结论:
- 开发的方法有效地提高了微生物细胞工厂中目标化合物的生产.
- 使用非重复性CDS和机器学习可以确保工程微生物的遗传稳定性.
- 这种方法为构建高效,稳定的微生物细胞工厂提供了强大的战略.
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