生物生产
合成生物学
清脆的
代谢工程
计算生物学
生物
控制(管理)
生化工程
计算机科学
生物技术
基因
工程类
人工智能
遗传学
作者
Xueqin Lv,Ángeles Hueso‐Gil,Xinyu Bi,Yaokang Wu,Yanfeng Liu,Long Liu,Rodrigo Ledesma‐Amaro
标识
DOI:10.1016/j.copbio.2022.102724
摘要
In industrial bioprocesses, microbial metabolism dictates the product yields, and therefore, our capacity to control it has an enormous potential to help us move towards a bio-based economy. The rapid development of multiomics data has accelerated our systematic understanding of complex metabolic regulatory mechanisms, which allow us to develop tools to manipulate them. In the last few years, machine learning-based metabolic modeling, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) derived synthetic biology tools, and synthetic genetic circuits have been widely used to control the metabolism of microorganisms, manipulate gene expression, and build synthetic pathways for bioproduction. This review describes the latest developments for metabolic control, and focuses on the trends and challenges of metabolic engineering strategies.
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