人工智能指导的基因融合延长了合成基因电路的进化半衰期
Itamar Menuhin-Gruman1, Matan Arbel-Groissman2, Doron Naki2
1Department of Biomedical Engineering, Tel Aviv University, Tel Aviv 6997801, Israel.
Science advances
|October 1, 2025
概括
合成生物学面临着基因表达稳定性的挑战. STABLES是一种新的基因融合策略,将感兴趣的基因与必要的基因联系起来,提高了工程生物的稳定性和生产力.
科学领域:
- 合成生物学 合成生物学
- 分子生物学分子生物学
- 生物技术是生物技术.
背景情况:
- 进化不稳定性经常导致合成生物学中异质基因表达的丧失.
- 这种不稳定性对工程生物的可靠应用构成了重大挑战.
研究的目的:
- 开发一种新的基因融合策略,STABLES,以增强工程生物体中基因表达的进化稳定性.
- 利用机器学习框架优化基因融合策略.
主要方法:
- 稳定策略:通过泄漏的停止码子将感兴趣的基因 (GOI) 与必要的内源基因 (EG) 联系起来.
- 机器学习框架:使用生物信息和生物物理特征预测最佳的GOI-EG对.
- 为增强稳定性和表达而优化DNA序列.
主要成果:
- 在*Saccharomyces cerevisiae*中进行的实验验证显示,稳定性和生产力显著改善.
- 对于表达光蛋白和人类亲胰岛素的成功应用.
- 证明了STABLES方法的可扩展性,适应性和无生物体性质.
结论:
- 在合成生物学中,STABLES提供了一个强大的解决方案来增强进化稳定性.
- 这种方法对工业生物技术和开发更稳定的工程菌株具有广泛的影响.
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