科斯米克-dFBA:一个新的多尺度混合框架用于生物过程建模
Saratram Gopalakrishnan1, William Johnson2, Miguel A Valderrama-Gomez2
1Department of Pediatrics, University of California San Diego, USA.
Metabolic engineering
|February 22, 2024
概括
我们开发了一种新的混合模型,COSMIC-dFBA,用于预测生物反应器中的细胞生长和抗体产生. 这种先进的建模方法显著提高了生物制造过程的预测准确性.
科学领域:
- 生物技术是生物技术.
- 代谢工程是代谢工程.
- 计算生物学 计算生物学
背景情况:
- 细胞代谢对于生物制造至关重要,推动细胞生长和生产力.
- 生物反应器中的动态代谢转变限制了传统机械模型的预测能力.
- 精确的建模对于优化生物工艺设计和控制至关重要.
研究的目的:
- 引入COSMIC-dFBA,一种新的混合多尺度建模范式.
- 提高动态流量平衡分析 (dFBA) 对生物反应器过程的预测能力.
- 准确预测细胞密度,抗体标位和代谢物度.
主要方法:
- 开发了COSMIC-dFBA,将机器学习与基因组规模的代谢模型集成在一起.
- 分解的代谢物吸收/分泌率从不同的细胞状态 (生长,抗体产生) 转化为贡献.
- 参数化模型使用随时可用的废媒体代谢物度.
主要成果:
- COSMIC-dFBA准确地预测了细胞密度和抗体标位在测量值的10%以内.
- 与标准dFBA相比显著改善:细胞密度为90%,抗体标位为72%.
- 成功模拟了生物反应器环境中的动态代谢变化.
结论:
- 混合COSMIC-dFBA框架有效地捕捉了生物反应器中的动态细胞代谢.
- 这种方法将dFBA的适用性扩展到复杂的,现实世界的生物制造条件.
- COSMIC-dFBA为生物过程优化和预测控制提供了一个强大的工具.
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