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

Yuyao Ren, Ewelina Celińska, Peng Cai* and Yongjin J. Zhou*, 
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Abstract

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.

结合定向酶进化与代谢工程开发高效微生物细胞工厂
合成生物学和代谢工程领域的蓬勃发展为微生物细胞工厂从可再生原料中可持续生产化学品提供了有前途的方法。经典的代谢工程策略主要集中在改变基因表达水平和酶浓度来改善特定途径的代谢通量。然而,酶性质的影响和局限性在经典代谢工程中通常被忽视,这可能会阻碍微生物细胞工厂的进一步优化。蛋白质工程和定向进化是修饰蛋白质以获得理想特性的有力工具,它们已被整合到代谢工程工作中,以构建高效的代谢途径和最佳的工业底盘。在此综述中,我们介绍了传统的和数据驱动的定向进化策略和技术,包括随机文库设计、半系统设计、智能文库设计和体内连续进化。我们还讨论了这些定向进化策略如何应用于代谢工程中,以实现通过简单的基因过表达或敲除无法实现的超表型。最后,我们讨论了在代谢工程中应用蛋白质工程的挑战,以及利用最新技术加速定向进化工作流程的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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