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A comparative survey of the influence of small self-cleaving ribozymes on gene expression in human cell culture.
Kläge, Dennis; Müller, Elisabeth; Hartig, Jörg S.
Afiliação
  • Kläge D; Department of Chemistry and Konstanz Research School Chemical Biology (KoRS-CB), University of Konstanz, Konstanz, Germany.
  • Müller E; Department of Chemistry and Konstanz Research School Chemical Biology (KoRS-CB), University of Konstanz, Konstanz, Germany.
  • Hartig JS; Department of Chemistry and Konstanz Research School Chemical Biology (KoRS-CB), University of Konstanz, Konstanz, Germany.
RNA Biol ; 21(1): 1-11, 2024 Jan.
Article em En | MEDLINE | ID: mdl-38146121
ABSTRACT
Self-cleaving ribozymes are versatile tools for synthetic biologists when it comes to controlling gene expression. Up to date, 12 different classes are known, and over the past decades more and more details about their structure, cleavage mechanisms and natural environments have been uncovered. However, when these motifs are applied to mammalian gene expression constructs, the outcome can often be unexpected. A variety of factors, such as surrounding sequences and positioning of the ribozyme influences the activity and hence performance of catalytic RNAs. While some information about the efficiency of individual ribozymes (each tested in specific contexts) is known, general trends obtained from standardized, comparable experiments are lacking, complicating decisions such as which ribozyme to choose and where to insert it into the target mRNA. In many cases, application-specific optimization is required, which can be very laborious. Here, we systematically compared different classes of ribozymes within the 3'-UTR of a given reporter gene. We then examined position-dependent effects of the best-performing ribozymes. Moreover, we tested additional variants of already widely used hammerhead ribozymes originating from various organisms. We were able to identify functional structures suited for aptazyme design and generated highly efficient hammerhead ribozyme variants originating from the human genome. The present dataset will aide decisions about how to apply ribozymes for affecting gene expression as well as for developing ribozyme-based switches for controlling gene expression in human cells.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: RNA Catalítico Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: RNA Catalítico Idioma: En Ano de publicação: 2024 Tipo de documento: Article