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

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 m...

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Autores principales:	Yu Wang, Haijiao Cheng, Yang Liu, Ye Liu, Xiao Wen, Kun Zhang, Xiaomeng Ni, Ning Gao, Liwen Fan, Zhihui Zhang, Jiao Liu, Jiuzhou Chen, Lixian Wang, Yanmei Guo, Ping Zheng, Meng Wang, Jibin Sun, Yanhe Ma
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/33779273c5a84abd9c7115b63093df48
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spelling	oai:doaj.org-article:33779273c5a84abd9c7115b63093df482021-12-02T13:24:04ZIn-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing10.1038/s41467-021-21003-y2041-1723https://doaj.org/article/33779273c5a84abd9c7115b63093df482021-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-21003-yhttps://doaj.org/toc/2041-1723To 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.Yu WangHaijiao ChengYang LiuYe LiuXiao WenKun ZhangXiaomeng NiNing GaoLiwen FanZhihui ZhangJiao LiuJiuzhou ChenLixian WangYanmei GuoPing ZhengMeng WangJibin SunYanhe MaNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Yu Wang Haijiao Cheng Yang Liu Ye Liu Xiao Wen Kun Zhang Xiaomeng Ni Ning Gao Liwen Fan Zhihui Zhang Jiao Liu Jiuzhou Chen Lixian Wang Yanmei Guo Ping Zheng Meng Wang Jibin Sun Yanhe Ma In-situ generation of large numbers of genetic combinations for metabolic reprogramming via CRISPR-guided base editing
description	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.
format	article
author	Yu Wang Haijiao Cheng Yang Liu Ye Liu Xiao Wen Kun Zhang Xiaomeng Ni Ning Gao Liwen Fan Zhihui Zhang Jiao Liu Jiuzhou Chen Lixian Wang Yanmei Guo Ping Zheng Meng Wang Jibin Sun Yanhe Ma
author_facet	Yu Wang Haijiao Cheng Yang Liu Ye Liu Xiao Wen Kun Zhang Xiaomeng Ni Ning Gao Liwen Fan Zhihui Zhang Jiao Liu Jiuzhou Chen Lixian Wang Yanmei Guo Ping Zheng Meng Wang Jibin Sun Yanhe Ma
author_sort	Yu Wang
title	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_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_sort	in-situ generation of large numbers of genetic combinations for metabolic reprogramming via crispr-guided base editing
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/33779273c5a84abd9c7115b63093df48
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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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