Comprehensive evaluation of the capacities of microbial cell factories

代谢工程 生化工程 代谢通量分析 代谢途径 合成生物学 异源的 计算机科学 工业微生物学 生产(经济) 代谢活性 焊剂(冶金) 生物技术 计算生物学 生物 化学 工程类 新陈代谢 生物化学 发酵 生物系统 经济 有机化学 宏观经济学 基因
作者
Gi Bae Kim,Hyung Kyu Kim,Sang Yup Lee
出处
期刊:Nature Communications [Springer Nature]
卷期号:16 (1) 被引量:12
标识
DOI:10.1038/s41467-025-58227-1
摘要

Systems metabolic engineering is facilitating the development of high-performing microbial cell factories for producing chemicals and materials. However, constructing an efficient microbial cell factory still requires exploring and selecting various host strains, as well as identifying the best-suited metabolic engineering strategies, which demand significant time, effort, and costs. Here, we comprehensively evaluate the capacities of various microbial cell factories and propose strategies for systems metabolic engineering steps, including host strain selection, metabolic pathway reconstruction, and metabolic flux optimization. We analyze the metabolic capacities of five representative industrial microorganisms as cell factories for the production of 235 different bio-based chemicals and suggest the most suitable host strain for the corresponding chemical production. To improve the innate metabolic capacity by constructing more efficient metabolic pathways, heterologous metabolic reactions, and cofactor exchanges are systematically analyzed. Additionally, we present metabolic engineering strategies, which include up- and down-regulation target reactions, for the improved production of chemicals. Altogether, this study will serve as a comprehensive resource for the systems metabolic engineering of microorganisms in the bio-based production of chemicals. Constructing an efficient microbial cell factory still requires exploring and selecting various host strains, as well as identifying the best-suited metabolic engineering strategies, which demand significant time, effort, and costs. Here the authors calculate the maximum yields of 235 bio-based chemicals in 5 different microbes, evaluated heterologous reactions and cofactor swaps, and predicted engineering strategies, providing a comprehensive resource for systems metabolic engineering.
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