Impact of Biomass constituents on Metabolic Flux Distribution in Escherichia coli

Flux balance analysis (FBA), a methodology used for estimation of cell behavior, requires biochemical reaction network of microorganisms. Within this network, biomass formation reaction plays an important role in estimation of fluxes since it affects the various pathways engaged in biosynthesis. Uncertainty in biomass constituents and their relevant coefficients can affect prediction of metabolic flux distribution. To examine how estimated flux distribution and growth rate are affected by this reaction, FBA was applied to E. coli core in this work for five different cases, namely original reaction (OR) of the model, scaled reaction (SR), scaled randomly changed coefficients of SRR (۲۰% allowable deviation from mean value) and SRBR (random number between ۰ and ۱) and scaled reaction with large deviations (SLR). Examination of OR revealed biomass formation of above ۱ g which was not conventional. Therefore, coefficients were normalized (SR) and this resulted in about ۳۷% increase in estimated maximized growth (۱.۱۹۲۵ h-۱) compared to that of OR (۰.۸۷۳۹ h-۱). This showed that imprecise biomass reaction leads to incorrect estimation of fluxes and the maximum value of the objective function. To evaluate the extent of flux deviations between examined cases, the flux deviation index (FDI) was used. An index of ۲۸.۳ was obtained for deviation of fluxes between cases SR and OR. SRR resulted in relatively low change (۰.۴۲%) in specific growth rate compared to SR, showing an index of ۱.۰۶۴۶. SRBR indicated a change of ۴.۱۳% in growth rate compared to SR with an index of ۱۲.۰۲۹۷, indicating greater changes in fluxes compared to those of SR. Finally, SLR led to ۲% change in growth rate compared to SR case with an index of ۶.۵. So, to obtain reliable flux distribution, biomass reaction needs special consideration with regards to both the overall stoichiometry and the compositions of various constituents

کلیدواژه ها:

Biomass formation reaction ، Biomass constituents ، Metabolic flux analysis ، Escherichia coli.