Strategies in engineering sustainable biochemical synthesis through microbial systems

被引:0
|
作者
Song, Yoseb [1 ]
Prather, Kristala L. J. [1 ]
机构
[1] MIT, Dept Chem Engn, Cambridge, MA 02139 USA
基金
美国国家科学基金会;
关键词
Metabolic engineering; Machine learning; Systems biology; Synthetic biology Microbe; Genome engineering; GENE-EXPRESSION;
D O I
10.1016/j.cbpa.2024.102493
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Growing environmental concerns and the urgency to address climate change have increased demand for the development of sustainable alternatives to fossil-derived fuels and chemicals. Microbial systems, possessing inherent biosynthetic capabilities, present a promising approach for achieving this goal. This review discusses the coupling of systems and synthetic biology to enable the elucidation and manipulation of microbial phenotypes for the production of chemicals that can substitute for petroleum-derived counterparts and contribute to advancing green biotechnology. The integration of artificial intelligence with metabolic engineering to facilitate precise and data-driven design of biosynthetic pathways is also discussed, along with the identification of current limitations and proposition of strategies for optimizing biosystems, thereby propelling the field of chemical biology towards sustainable chemical production.
引用
收藏
页数:9
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