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Software-based screening for efficient sgRNAs in Lactococcus lactis.
Wang, Hui; Ai, Lianzhong; Xia, Yongjun; Wang, Guangqiang; Xiong, Zhiqiang; Song, Xin.
Afiliação
  • Wang H; Shanghai Engineering Research Center of Food Microbiology, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Ai L; Shanghai Engineering Research Center of Food Microbiology, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Xia Y; Shanghai Engineering Research Center of Food Microbiology, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Wang G; Shanghai Engineering Research Center of Food Microbiology, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Xiong Z; Shanghai Engineering Research Center of Food Microbiology, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Song X; Shanghai Engineering Research Center of Food Microbiology, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
J Sci Food Agric ; 104(2): 1200-1206, 2024 Jan 30.
Article em En | MEDLINE | ID: mdl-37647419
ABSTRACT

BACKGROUND:

The two essential editing elements in the clustered regularly interspaced short palindromic repeats (CRISPR) editing system are promoter and single-guide RNA (sgRNA), the latter of which determines whether Cas protein can precisely target a specific location to edit the targeted gene. Therefore, the selection of sgRNA is crucial to the efficiency of the CRISPR editing system. Various online prediction tools for sgRNA are currently available. These tools can predict all possible sgRNAs of the targeted gene and rank sgRNAs according to certain scoring criteria according to the demands of the user.

RESULTS:

We designed sgRNAs for Lactococcus lactis NZ9000 LLNZ_RS02020 (ldh) and LLNZ_RS10925 (upp) individually using online prediction software - CRISPOR - and successfully constructed a series of knockout strains to allow comparison of the knockout efficiency of each sgRNA and analyze the differences between software predictions and actual experimental results.

CONCLUSION:

Our experimental results showed that the actual editing efficiency of the screened sgRNAs did not match the predicted results - a phenomenon that suggests that established findings from eukaryotic studies are not universally applicable to prokaryotes. Software prediction can still be used as a tool for the initial screening of sgRNAs before further selection of suitable sgRNAs through experimental experience. © 2023 Society of Chemical Industry.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Lactococcus lactis / Edição de Genes Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Lactococcus lactis / Edição de Genes Idioma: En Ano de publicação: 2024 Tipo de documento: Article