BMC Systems Biology 2012, 6:42
Published: 14 May 2012
Genome-scale metabolic networks and flux models are an effective platform for linking
an organism genotype to its phenotype. However, few modeling approaches offer predictive
capabilities to evaluate potential metabolic engineering strategies in silico.
A new method called “
nalysis with flux
s (FBrAtio)” was developed in this research and applied to a new genome-scale model
of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model
wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were
required. The FBrAtio approach allowed solutions to be found through standard linear
programming. Five flux ratio constraints were required to achieve a qualitative picture
of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v)
butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and
show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone
selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase
greatly increases ethanol production.
FBrAtio is a promising new method for constraining genome-scale models using internal
flux ratios. The method was effective for modeling wild-type and engineered strains
of C. acetobutylicum.