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Engineering repressors with coevolutionary cues facilitates toggle switches with a master reset.
Dimas, Rey P; Jiang, Xian-Li; Alberto de la Paz, Jose; Morcos, Faruck; Chan, Clement T Y.
Afiliação
  • Dimas RP; Department of Biology, The University of Texas at Tyler, Tyler, TX 75799, USA.
  • Jiang XL; Department of Biological Sciences, The University of Texas at Dallas, Dallas, TX 75080, USA.
  • Alberto de la Paz J; Department of Biological Sciences, The University of Texas at Dallas, Dallas, TX 75080, USA.
  • Morcos F; Department of Biological Sciences, The University of Texas at Dallas, Dallas, TX 75080, USA.
  • Chan CTY; Department of Bioengineering, The University of Texas at Dallas, Dallas, TX 75080, USA.
Nucleic Acids Res ; 47(10): 5449-5463, 2019 06 04.
Article em En | MEDLINE | ID: mdl-31162606
ABSTRACT
Engineering allosteric transcriptional repressors containing an environmental sensing module (ESM) and a DNA recognition module (DRM) has the potential to unlock a combinatorial set of rationally designed biological responses. We demonstrated that constructing hybrid repressors by fusing distinct ESMs and DRMs provides a means to flexibly rewire genetic networks for complex signal processing. We have used coevolutionary traits among LacI homologs to develop a model for predicting compatibility between ESMs and DRMs. Our predictions accurately agree with the performance of 40 engineered repressors. We have harnessed this framework to develop a system of multiple toggle switches with a master OFF signal that produces a unique behavior each engineered biological activity is switched to a stable ON state by different chemicals and returned to OFF in response to a common signal. One promising application of this design is to develop living diagnostics for monitoring multiple parameters in complex physiological environments and it represents one of many circuit topologies that can be explored with modular repressors designed with coevolutionary information.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Processamento de Sinais Assistido por Computador / Engenharia de Proteínas / Biologia Sintética / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Nucleic Acids Res Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Processamento de Sinais Assistido por Computador / Engenharia de Proteínas / Biologia Sintética / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Nucleic Acids Res Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos