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Designing RNA-based genetic control systems for efficient production from engineered metabolic pathways.
Stevens, Jason T; Carothers, James M.
Afiliação
  • Stevens JT; Departments of Chemical Engineering and Bioengineering, Molecular Engineering & Sciences Institute, and Center for Synthetic Biology, University of Washington , Seattle, Washington 98195, United States.
ACS Synth Biol ; 4(2): 107-15, 2015 Feb 20.
Article em En | MEDLINE | ID: mdl-25314371
ABSTRACT
Engineered metabolic pathways can be augmented with dynamic regulatory controllers to increase production titers by minimizing toxicity and helping cells maintain homeostasis. We investigated the potential for dynamic RNA-based genetic control systems to increase production through simulation analysis of an engineered p-aminostyrene (p-AS) pathway in E. coli. To map the entire design space, we formulated 729 unique mechanistic models corresponding to all of the possible control topologies and mechanistic implementations in the system under study. Two thousand sampled simulations were performed for each of the 729 system designs to relate the potential effects of dynamic control to increases in p-AS production (total of 3 × 10(6) simulations). Our analysis indicates that dynamic control strategies employing aptazyme-regulated expression devices (aREDs) can yield >10-fold improvements over static control. We uncovered generalizable trends in successful control architectures and found that highly performing RNA-based control systems are experimentally tractable. Analyzing the metabolic control state space to predict optimal genetic control strategies promises to enhance the design of metabolic pathways.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: RNA / Escherichia coli / Engenharia Metabólica Tipo de estudo: Prognostic_studies Idioma: En Revista: ACS Synth Biol Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: RNA / Escherichia coli / Engenharia Metabólica Tipo de estudo: Prognostic_studies Idioma: En Revista: ACS Synth Biol Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos