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Structural Bistability of the GAL Regulatory Network and Characterization of its Domains of Attraction.

Authors :
Cosentino, Carlo
Salerno, Luca
Passanti, Antonio
Merola, Alessio
Bates, Declan G.
Amato, Francesco
Source :
Journal of Computational Biology. Feb2012, Vol. 19 Issue 2, p148-162. 15p.
Publication Year :
2012

Abstract

Bistability is a system-level property, exploited by many biomolecular interaction networks as a key mechanism to accomplish different cellular functions (e.g., differentiation, cell cycle, switch-like response to external stimuli). Bistability has also been experimentally found to occur in the regulatory network of the galactose metabolic pathway in the model organism Saccharomyces cerevisiae. In this yeast, bistability generates a persistent memory of the type of carbon source available in the extracellular medium: under the same experimental conditions, cells previously grown with different nutrients generate different responses and get stably locked into two distinct steady states. The molecular interactions of the GAL regulatory network have been thoroughly dissected through wet-lab experiments; thus, this system provides a formidable benchmark to our ability to characterize and reproduce in silico the behavior of bistable biological systems. To this aim, a number of models have been proposed in the literature; however, we found that they are not able to replicate the persistent memory behavior observed in (Acar et al., ). The present study proposes a novel model of the GAL regulatory network, which, in addition to reproducing in silico the experimental findings, can be formally analyzed for structural multistability of the network, using chemical reaction network theory (CRNT), and allows the characterization of the domains of attraction (DA). This work provides further insights into the GAL system and proposes an easily generalizable approach to the study of bistability-associated behaviors in biological systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10665277
Volume :
19
Issue :
2
Database :
Academic Search Index
Journal :
Journal of Computational Biology
Publication Type :
Academic Journal
Accession number :
91277076
Full Text :
https://doi.org/10.1089/cmb.2011.0251