Improved computational performance of MFA using elementary metabolite units and flux coupling.
Metab Eng
; 12(2): 123-8, 2010 Mar.
Article
en En
| MEDLINE
| ID: mdl-19837183
ABSTRACT
Extending the scope of isotope mapping models becomes increasingly important in order to analyze strains and drive improved product yields as more complex pathways are engineered into strains and as secondary metabolites are used as starting points for new products. Here we present how the elementary metabolite unit (EMU) framework and flux coupling significantly decrease the computational burden of metabolic flux analysis (MFA) when applied to large-scale metabolic models. We applied these techniques to a previously published isotope mapping model of Escherichia coli accounting for 238 reactions. We find that the combined use of EMU and flux coupling analysis leads to a ten-fold decrease in the number of variables in comparison to the original isotope distribution vector (IDV) version of the model. In addition, using OptMeas the task of identifying additional measurement choices to fully specify the flows in the metabolic network required only 2% of the computation time of the one using IDVs. The observed computational savings reveal the rapid progress in performing MFA with increasingly larger isotope models with the ultimate goal of handling genome-scale models of metabolism.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Biología Computacional
/
Escherichia coli
/
Redes y Vías Metabólicas
/
Modelos Biológicos
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Metab Eng
Asunto de la revista:
ENGENHARIA BIOMEDICA
/
METABOLISMO
Año:
2010
Tipo del documento:
Article
País de afiliación:
Estados Unidos