Yf. Ko et al., A METABOLIC MODEL OF CELLULAR ENERGETICS AND CARBON FLUX DURING AEROBIC ESCHERICHIA-COLI FERMENTATION, Biotechnology and bioengineering, 43(9), 1994, pp. 847-855
An integrated metabolic model for the production of acetate by Escheri
chia coli growing on glucose under aerobic conditions was presented pr
eviously (Ko et al., 1993). The resulting model equations can be used
to explain phenomena often observed with industrial fermentations, i.e
., increased acetate production which follows from high glucose uptake
rate, a low dissolved oxygen concentration, a high specific growth ra
te, or a combination of these conditions. However, several questions s
till need to be addressed. First, cell composition is growth rate and
media dependent. Second, the macromolecular composition varied between
E. coli strains. And finally, a model that represents the carbon flux
es between the Embden - Meyerhof- Parnas (EMP) and the hexose monophos
phate (HMP) pathways when cells are subject to internal and/or externa
l stresses is still not well defined. In the present work, we have mad
e an effort to account for these effects, and the resulting model equa
tions show good agreement for wild-type and recombinant E. coil experi
mental data for the acetate concentration, the onset of acetate secret
ion, and cell yield based on glucose. These results are useful for opt
imizing aerobic E. coil fermentation processes. More specifically, we
have determined the EMP pathway carbon flux profiles required by the i
ntegrated metabolic model for an accurate fit of the acetic acid profi
le data from a wild-type E. coli strain ML308. These EMP carbon flux p
rofiles were correlated with a dimensionless measurement of biomass an
d then used to predict the acetic acid profiles for E. coli strain F-1
22 expressing human immunodeficiency virus-(HIV528) beta-galactosidase
fusion protein. The effect of different macromolecular compositions a
nd growth rates between these two E. coli strains required a constant
scaling factor for improved quantitative predictions. (C) 1994 John Wi
ley and Sons, Inc.