Cell factory design with advanced metabolic modelling empowered by artificial intelligence

代谢工程 合成生物学 生化工程 底盘 代谢网络 计算机科学 计算模型 人工智能 生物技术 工程类 计算生物学 生物 机械工程 生物化学
作者
Hongzhong Lu,L.-j. Xiao,Wenbin Liao,Xuefeng Yan,Jens Nielsen
出处
期刊:Metabolic Engineering [Elsevier BV]
卷期号:85: 61-72
标识
DOI:10.1016/j.ymben.2024.07.003
摘要

Advances in synthetic biology and artificial intelligence (AI) have provided new opportunities for modern biotechnology. High-performance cell factories, the backbone of industrial biotechnology, are ultimately responsible for determining whether a bio-based product succeeds or fails in the fierce competition with petroleum-based products. To date, one of the greatest challenges in synthetic biology is the creation of high-performance cell factories in a consistent and efficient manner. As so-called white-box models, numerous metabolic network models have been developed and used in computational strain design. Moreover, great progress has been made in AI-powered strain engineering in recent years. Both approaches have advantages and disadvantages. Therefore, the deep integration of AI with metabolic models is crucial for the construction of superior cell factories with higher titres, yields and production rates. The detailed applications of the latest advanced metabolic models and AI in computational strain design are summarized in this review. Additionally, approaches for the deep integration of AI and metabolic models are discussed. It is anticipated that advanced mechanistic metabolic models powered by AI will pave the way for the efficient construction of powerful industrial chassis strains in the coming years.
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