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Bistability and Asynchrony in a Boolean Model of the L-arabinose Operon in Escherichia coli.
Jenkins, Andy; Macauley, Matthew.
Afiliação
  • Jenkins A; Department of Mathematics, University of Georgia, Athens, GA, USA.
  • Macauley M; Department of Mathematical Sciences, Clemson University, Clemson, SC, USA. macaule@clemson.edu.
Bull Math Biol ; 79(8): 1778-1795, 2017 Aug.
Article em En | MEDLINE | ID: mdl-28639170
The lactose operon in Escherichia coli was the first known gene regulatory network, and it is frequently used as a prototype for new modeling paradigms. Historically, many of these modeling frameworks use differential equations. More recently, Stigler and Veliz-Cuba proposed a Boolean model that captures the bistability of the system and all of the biological steady states. In this paper, we model the well-known arabinose operon in E. coli with a Boolean network. This has several complex features not found in the lac operon, such as a protein that is both an activator and repressor, a DNA looping mechanism for gene repression, and the lack of inducer exclusion by glucose. For 11 out of 12 choices of initial conditions, we use computational algebra and Sage to verify that the state space contains a single fixed point that correctly matches the biology. The final initial condition, medium levels of arabinose and no glucose, successfully predicts the system's bistability. Finally, we compare the state space under synchronous and asynchronous update and see that the former has several artificial cycles that go away under a general asynchronous update.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Óperon / Arabinose / Escherichia coli Tipo de estudo: Prognostic_studies Idioma: En Revista: Bull Math Biol Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Óperon / Arabinose / Escherichia coli Tipo de estudo: Prognostic_studies Idioma: En Revista: Bull Math Biol Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos