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GeneReg: a constraint-based approach for design of feasible metabolic engineering strategies at the gene level.
Razaghi-Moghadam, Zahra; Nikoloski, Zoran.
Afiliación
  • Razaghi-Moghadam Z; Department of Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany.
  • Nikoloski Z; Department of Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany.
Bioinformatics ; 37(12): 1717-1723, 2021 07 19.
Article en En | MEDLINE | ID: mdl-33245091
ABSTRACT
MOTIVATION Large-scale metabolic models are widely used to design metabolic engineering strategies for diverse biotechnological applications. However, the existing computational approaches focus on alteration of reaction fluxes and often neglect the manipulations of gene expression to implement these strategies.

RESULTS:

Here, we find that the association of genes with multiple reactions leads to infeasibility of engineering strategies at the flux level, since they require contradicting manipulations of gene expression. Moreover, we identify that all of the existing approaches to design gene knockout strategies do not ensure that the resulting design may also require other gene alterations, such as up- or downregulations, to match the desired flux distribution. To address these issues, we propose a constraint-based approach, termed GeneReg, that facilitates the design of feasible metabolic engineering strategies at the gene level and that is readily applicable to large-scale metabolic networks. We show that GeneReg can identify feasible strategies to overproduce ethanol in Escherichia coli and lactate in Saccharomyces cerevisiae, but overproduction of the TCA cycle intermediates is not feasible in five organisms used as cell factories under default growth conditions. Therefore, GeneReg points at the need to couple gene regulation and metabolism to design rational metabolic engineering strategies. AVAILABILITY AND IMPLEMENTATION https//github.com/MonaRazaghi/GeneReg. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Redes y Vías Metabólicas / Ingeniería Metabólica Tipo de estudio: Prognostic_studies Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Redes y Vías Metabólicas / Ingeniería Metabólica Tipo de estudio: Prognostic_studies Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Alemania