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Automated design of gene circuits with optimal mushroom-bifurcation behavior.
Otero-Muras, Irene; Perez-Carrasco, Ruben; Banga, Julio R; Barnes, Chris P.
Afiliação
  • Otero-Muras I; Computational Synthetic Biology Group. Institute for Integrative Systems Biology (UV, CSIC), Spanish National Research Council, 46980 Valencia, Spain.
  • Perez-Carrasco R; Department of Life Sciences. Imperial College London, London, UK.
  • Banga JR; Computational Biology Lab, MBG-CSIC, Spanish National Research Council, 36143 Pontevedra, Spain.
  • Barnes CP; Department of Cell and Developmental Biology, University College London, London, UK.
iScience ; 26(6): 106836, 2023 Jun 16.
Article em En | MEDLINE | ID: mdl-37255663
ABSTRACT
Recent advances in synthetic biology are enabling exciting technologies, including the next generation of biosensors, the rational design of cell memory, modulated synthetic cell differentiation, and generic multifunctional biocircuits. These novel applications require the design of gene circuits leading to sophisticated behaviors and functionalities. At the same time, designs need to be kept minimal to avoid compromising cell viability. Bifurcation theory addresses such challenges by associating circuit dynamical properties with molecular details of its design. Nevertheless, incorporating bifurcation analysis into automated design processes has not been accomplished yet. This work presents an optimization-based method for the automated design of synthetic gene circuits with specified bifurcation diagrams that employ minimal network topologies. Using this approach, we designed circuits exhibiting the mushroom bifurcation, distilled the most robust topologies, and explored its multifunctional behavior. We then outline potential applications in biosensors, memory devices, and synthetic cell differentiation.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: IScience Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: IScience Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Espanha