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In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
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In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
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In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing

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In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
Journal Article

In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing

2021
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Overview
Reprogramming complex cellular metabolism requires simultaneous regulation of multigene expression. Ex-situ cloning-based methods are commonly used, but the target gene number and combinatorial library size are severely limited by cloning and transformation efficiencies. In-situ methods such as multiplex automated genome engineering (MAGE) depends on high-efficiency transformation and incorporation of heterologous DNA donors, which are limited to few microorganisms. Here, we describe a Base Editor-Targeted and Template-free Expression Regulation (BETTER) method for simultaneously diversifying multigene expression. BETTER repurposes CRISPR-guided base editors and in-situ generates large numbers of genetic combinations of diverse ribosome binding sites, 5’ untranslated regions, or promoters, without library construction, transformation, and incorporation of DNA donors. We apply BETTER to simultaneously regulate expression of up to ten genes in industrial and model microorganisms Corynebacterium glutamicum and Bacillus subtilis . Variants with improved xylose catabolism, glycerol catabolism, or lycopene biosynthesis are respectively obtained. This technology will be useful for large-scale fine-tuning of multigene expression in both genetically tractable and intractable microorganisms. To obtain optimal yield and productivity in bioproduction, expression of pathway genes must be appropriately coordinated. Here, the authors report repurposing of base editors for simultaneous regulation of multiple gene expression and demonstrate its application in industrially important and model microorganisms.