在培养肉类中基因组规模的代谢模型:进步,挑战和未来的方向
Sandra Gomez Romero1, Isabella Spielmann2, Nanette Boyle3
1Quantitative Biosciences and Engineering, Colorado School of Mines, Golden, CO, USA.
Current opinion in biotechnology
|May 16, 2025
概括
基因组规模的代谢模型 (GEMs) 可以通过解决代谢挑战并实现无血清介质来优化培养肉类生产. 这种方法增强生物质生产,为传统肉类提供可持续和可扩展的替代品.
科学领域:
- 生物技术是生物技术.
- 细胞农业 细胞农业
- 代谢工程是代谢工程.
背景情况:
- 培养肉类为传统肉类提供了可持续的替代品,但面临着诸如无血清介质要求和生长条件优化等代谢挑战.
- 基因组规模代谢模型 (GEMs) 是优化生物制造中的细胞代谢的强大工具,已成功应用于中国仓鼠卵巢细胞.
- 适应培养肉类的GEM可以解决关键的代谢障碍,提高生产效率.
研究的目的:
- 探索基因组规模代谢模型 (GEMs) 在克服培养肉类生产中的代谢挑战中的应用.
- 展示GEM如何为培养肉类提供成本效益高,无血清介质的转型.
- 突出GEM在提高生物质生产和培养肉的整体可扩展性方面的潜力.
主要方法:
- 使用基因组规模代谢模型 (GEMs) 衍生出的代谢流量分析.
- 从生物制造 (例如,中国仓鼠卵巢细胞) 调整已建立的GEM,用于培养肉类应用.
- 将多omics数据 (转录组,蛋白组) 与GEM集成,以提高预测准确度.
主要成果:
- 在肉类培养系统中,GEM可以确定细胞生长和生物质生产的最佳代谢条件.
- 应用GEM有助于开发具有成本效益的无血清培养基.
- 由GEMs指导的代谢工程策略可以显著提高养殖肉类生产的效率.
结论:
- 基因组规模的代谢模型 (GEMs) 对于克服培养肉类生产中的代谢限制至关重要.
- 利用GEM可以开发可扩展,可持续和经济可行的养殖肉类.
- 未来的研究应该集中在扩大代谢数据集和整合多omics数据,以完善培养肉的GEM.
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