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

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 mult...

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Autores principales: Wang, Yu, Cheng, Haijiao, Liu, Yang, Liu, Ye, Wen, Xiao, Zhang, Kun, Ni, Xiaomeng, Gao, Ning, Fan, Liwen, Zhang, Zhihui, Liu, Jiao, Chen, Jiuzhou, Wang, Lixian, Guo, Yanmei, Zheng, Ping, Wang, Meng, Sun, Jibin, Ma, Yanhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846839/
https://www.ncbi.nlm.nih.gov/pubmed/33514753
http://dx.doi.org/10.1038/s41467-021-21003-y
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author Wang, Yu
Cheng, Haijiao
Liu, Yang
Liu, Ye
Wen, Xiao
Zhang, Kun
Ni, Xiaomeng
Gao, Ning
Fan, Liwen
Zhang, Zhihui
Liu, Jiao
Chen, Jiuzhou
Wang, Lixian
Guo, Yanmei
Zheng, Ping
Wang, Meng
Sun, Jibin
Ma, Yanhe
author_facet Wang, Yu
Cheng, Haijiao
Liu, Yang
Liu, Ye
Wen, Xiao
Zhang, Kun
Ni, Xiaomeng
Gao, Ning
Fan, Liwen
Zhang, Zhihui
Liu, Jiao
Chen, Jiuzhou
Wang, Lixian
Guo, Yanmei
Zheng, Ping
Wang, Meng
Sun, Jibin
Ma, Yanhe
author_sort Wang, Yu
collection PubMed
description 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.
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spelling pubmed-78468392021-02-08 In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing Wang, Yu Cheng, Haijiao Liu, Yang Liu, Ye Wen, Xiao Zhang, Kun Ni, Xiaomeng Gao, Ning Fan, Liwen Zhang, Zhihui Liu, Jiao Chen, Jiuzhou Wang, Lixian Guo, Yanmei Zheng, Ping Wang, Meng Sun, Jibin Ma, Yanhe Nat Commun Article 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. Nature Publishing Group UK 2021-01-29 /pmc/articles/PMC7846839/ /pubmed/33514753 http://dx.doi.org/10.1038/s41467-021-21003-y Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Wang, Yu
Cheng, Haijiao
Liu, Yang
Liu, Ye
Wen, Xiao
Zhang, Kun
Ni, Xiaomeng
Gao, Ning
Fan, Liwen
Zhang, Zhihui
Liu, Jiao
Chen, Jiuzhou
Wang, Lixian
Guo, Yanmei
Zheng, Ping
Wang, Meng
Sun, Jibin
Ma, Yanhe
In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
title In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
title_full In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
title_fullStr In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
title_full_unstemmed In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
title_short In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
title_sort in-situ generation of large numbers of genetic combinations for metabolic reprogramming via crispr-guided base editing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846839/
https://www.ncbi.nlm.nih.gov/pubmed/33514753
http://dx.doi.org/10.1038/s41467-021-21003-y
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