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  4. Combing Directed Enzyme Evolution with Metabolic Engineering to Develop Efficient Microbial Cell Factories
 
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Combing Directed Enzyme Evolution with Metabolic Engineering to Develop Efficient Microbial Cell Factories

Type
Journal article
Language
English
Date issued
2025
Author
Ren, Yuyao
Celińska, Ewelina 
Cai, Peng
Zhou, Yongjin J.
Faculty
Wydział Nauk o Żywności i Żywieniu
Journal
Chemical and Biological Engineers
ISSN
2836-967X
DOI
10.1021/cbe.5c00002
Web address
https://pubs.acs.org/doi/10.1021/cbe.5c00002
Volume
2
Number
8
Pages from-to
449-459
Abstract (EN)
The booming field of synthetic biology and metabolic engineering provides promising approaches for sustainable manufacturing of chemicals from renewable feedstocks with microbial cell factories. Classical metabolic engineering strategies mainly focus on altering gene expression levels and enzyme concentrations to improve the metabolic fluxes of specific pathways. However, the impact and limitations of enzyme properties, which are usually ignored in classical metabolic engineering efforts, can hinder further optimization of microbial cell factories. Protein engineering and directed evolution are powerful tools for modifying proteins to achieve desirable properties, and they have been integrated into metabolic engineering efforts to build highly efficient metabolic pathways and optimal industrial chassis. In this review, we present traditional and data-driven strategies and techniques of directed evolution, including random library design, semirational design, smart library design, and in vivo continuous evolution. We also discuss how these directed evolution strategies have been applied in metabolic engineering toward superphenotypes that cannot be achieved through simple gene overexpression or knockout. Finally, we discuss the challenges of applying protein engineering in metabolic engineering and the prospects for accelerating the directed evolution workflow using the state-of-art technologies.
Keywords (EN)
  • protein engineering

  • metabolic engineering

  • directed evolution

  • in vivo evolution

  • artificial intelligence

License
cc-by-nc-ndcc-by-nc-nd CC-BY-NC-ND - Attribution-NonCommercial-NoDerivatives
Open access date
May 1, 2025
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