Synthetic small regulatory RNAs in microbial metabolic engineering
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MINI-REVIEW
Synthetic small regulatory RNAs in microbial metabolic engineering Wen-Hai Xie 1,2 & Hong-Kuan Deng 1 & Jie Hou 1 & Li-Juan Wang 1,2 Received: 16 August 2020 / Revised: 15 October 2020 / Accepted: 21 October 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Small regulatory RNAs (sRNAs) finely control gene expression in prokaryotes and synthetic sRNA has become a useful highthroughput approach to tackle current challenges in metabolic engineering because of its many advantages compared to conventional gene knockouts. In this review, we first focus on the modular structures of sRNAs and rational design strategies of synthetic sRNAs on the basis of their modular structures. The wide applications of synthetic sRNAs in bacterial metabolic engineering, with or without the aid of heterogeneously expressed Hfq protein, were also covered. In addition, we give attention to the improvements in implementing synthetic sRNAs, which make the synthetic sRNA strategy universally applicable in metabolic engineering and synthetic biology. Key points • Synthetic sRNAs can be rationally designed based on modular structures of natural sRNAs. • Synthetic sRNAs were widely used for metabolic engineering in various microorganisms. • Several technological improvements made the synthetic sRNA strategy more applicable. Keywords Small regulatory RNA . Synthetic sRNA . Gene knockdown . Synthetic sRNA applications . Synthetic sRNA improvements . Metabolic engineering
Introduction Metabolic engineering has emerged as a crucial strategy for manipulating bacteria to produce high yields of chemicals and materials (Lee et al. 2012; Na et al. 2013; Biz et al. 2019). To achieve this objective, building or re-building metabolic pathways is needed to drive the microbial nutrient flux toward the desired bioproducts (Keasling 1999; Si et al. 2015; Nielsen and Keasling 2016). Given that intracellular robust metabolic networks are tightly regulated and highly optimized through evolution, developing new cell factories is still challenging (Si et al. 2015; Nielsen and Keasling 2016; Ren et al. 2020). Traditional Wen-Hai Xie and Hong-Kuan Deng contributed equally to this work. * Li-Juan Wang [email protected] 1
School of Life Sciences, Shandong University of Technology, Zibo 250049, China
2
Institute of Biomedical Research, Shandong Provincial Research Center for Bioinformatics Engineering and Technique, Zibo Key Laboratory of New Drug Development of Neurodegenerative diseases, Shandong University of Technology, Zibo, China
protein-based transcriptional control strategies can only modulate a small number of genes (Marcheschi et al. 2013; Wang et al. 2014; Hu et al. 2019). Selection of potential target genes at the genomic level and coordination of gene expression are essential for constructing superior metabolically engineered strains (Na et al. 2013; Si et al. 2015; Yang et al. 2018; Ren et al. 2020). Several genome-scale editing or engineering technologies have been developed and used to improve product format
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