Modeling leucine's metabolic pathway and ...
Type de document :
Article dans une revue scientifique: Article original
DOI :
URL permanente :
Titre :
Modeling leucine's metabolic pathway and knockout prediction improving the production of surfactin, a biosurfactant from Bacillus subtilis
Auteur(s) :
Coutte, Francois [Auteur]
Institut Charles Viollette (ICV) - EA 7394 [ICV]
Niehren, Joachim [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Dhali, Debarun [Auteur]
Institut Charles Viollette (ICV) - EA 7394 [ICV]
John, Mathias [Auteur]
BioComputing
Versari, Cristian [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Jacques, Philippe [Auteur]
Institut Charles Viollette (ICV) - EA 7394 [ICV]
Institut Charles Viollette (ICV) - EA 7394 [ICV]
Niehren, Joachim [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Dhali, Debarun [Auteur]
Institut Charles Viollette (ICV) - EA 7394 [ICV]
John, Mathias [Auteur]
BioComputing
Versari, Cristian [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Jacques, Philippe [Auteur]
Institut Charles Viollette (ICV) - EA 7394 [ICV]
Titre de la revue :
Biotechnology Journal
Numéro :
10
Pagination :
1216-34
Date de publication :
2015-08
Mot(s)-clé(s) en anglais :
Abstract interpretation
Qualitative reasonning
Metabolic networks
Modeling language
Bacillus subtilis
Knockout prediction
Systems biology
Surfactin
Qualitative reasonning
Metabolic networks
Modeling language
Bacillus subtilis
Knockout prediction
Systems biology
Surfactin
Discipline(s) HAL :
Informatique [cs]/Bio-informatique [q-bio.QM]
Résumé en anglais : [en]
A Bacillus subtilis mutant strain overexpressing surfactin biosynthetic genes was previously constructed. In order to further increase the production of this biosurfactant, our hypothesis is that the surfactin precursors, ...
Lire la suite >A Bacillus subtilis mutant strain overexpressing surfactin biosynthetic genes was previously constructed. In order to further increase the production of this biosurfactant, our hypothesis is that the surfactin precursors, especially leucine, must be overproduced. We present a three step approach for leucine overproduction directed by methods from computational biology. Firstly, we develop a new algorithm for gene knockout prediction based on abstract interpretation, which applies to a recent modeling language for reaction networks with partial kinetic information. Secondly, we model the leucine metabolic pathway as a reaction network in this language, and apply the knockout prediction algorithm with the target of leucine overproduction. Out of the 21 reactions corresponding to potential gene knockouts, the prediction algorithm selects 12 reactions. Six knockouts were introduced in B. subtilis 168 derivatives strains to verify their effects on surfactin production. For all generated mutants, the specific surfactin production is increased from 1.6- to 20.9-fold during the exponential growth phase, depending on the medium composition. These results show the effectiveness of the knockout prediction approach based on formal models for metabolic reaction networks with partial kinetic information, and confirms our hypothesis that precursors supply is one of the main parameters to optimize surfactin overproduction.Lire moins >
Lire la suite >A Bacillus subtilis mutant strain overexpressing surfactin biosynthetic genes was previously constructed. In order to further increase the production of this biosurfactant, our hypothesis is that the surfactin precursors, especially leucine, must be overproduced. We present a three step approach for leucine overproduction directed by methods from computational biology. Firstly, we develop a new algorithm for gene knockout prediction based on abstract interpretation, which applies to a recent modeling language for reaction networks with partial kinetic information. Secondly, we model the leucine metabolic pathway as a reaction network in this language, and apply the knockout prediction algorithm with the target of leucine overproduction. Out of the 21 reactions corresponding to potential gene knockouts, the prediction algorithm selects 12 reactions. Six knockouts were introduced in B. subtilis 168 derivatives strains to verify their effects on surfactin production. For all generated mutants, the specific surfactin production is increased from 1.6- to 20.9-fold during the exponential growth phase, depending on the medium composition. These results show the effectiveness of the knockout prediction approach based on formal models for metabolic reaction networks with partial kinetic information, and confirms our hypothesis that precursors supply is one of the main parameters to optimize surfactin overproduction.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
INRA
ISA
Univ. Artois
Univ. Littoral Côte d’Opale
INRA
ISA
Univ. Artois
Univ. Littoral Côte d’Opale
Collections :
Date de dépôt :
2019-09-26T08:28:13Z
2020-02-11T10:47:32Z
2020-02-11T10:47:32Z
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