为工业规模生产生物基分子优化菌株工程过程
Eric Abbate1, Jennifer Andrion1, Amanda Apel1
1Inscripta, Inc., 5720 Stoneridge Dr, Suite 300, Pleasanton, CA 94588, USA.
Journal of industrial microbiology & biotechnology
|September 1, 2023
概括
优化整个设计-制造-测试-学习周期,而不仅仅是个别步骤,是减少生物制造菌株开发成本和时间的关键. 整合计算设计,高吞吐量方法和机器学习加速了生物经济.
科学领域:
- 生物技术是生物技术.
- 合成生物学 合成生物学
- 代谢工程是代谢工程.
背景情况:
- 不断增长的生物经济依赖于高性能微生物菌株的高效生物制造.
- 设计-构建-测试-学习 (DBTL) 框架是应变工程的标准方法.
- 目前的DBTL周期面临时间和成本效益的限制,尽管吞吐量有所改善.
研究的目的:
- 提出一个综合的方法来优化整个DBTL循环在应变工程.
- 解决工业菌株开发的挑战,以减少成本和时间.
- 利用计算设计,高通量方法和机器学习方面的进步.
主要方法:
- 整合DBTL周期的所有四个阶段.
- 使用计算设计工具来开发菌株.
- 采用高通量基因组工程和表型化.
- 应用机器学习来预测应变扩大性能.
主要成果:
- 证明成功的菌株工程生产异质蛋白质,氨基酸和小分子.
- 在应变耐受性和健身方面表现出改善.
- 突出了减少工业压力的扩大风险的方法.
结论:
- 综合的DBTL方法对于彻底减少菌株开发时间和成本至关重要.
- 利用计算和机器学习工具可以提高生物制造的效率.
- 优化整个循环对于未来生物经济的成功至关重要.
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