The aim of this study was to design a robust parameter identification algorithm to characterize the effect of gene deletion on Escherichia coli (E. coli) MG1655. Two genes (pta and poxB) in the competitive pathways were deleted from this microorganism to inhibit pyruvate consumption. This condition deviated the E. coli metabolism toward the Krebs cycle. As a consequence, the biomass, substrate (glucose), lactic, and acetate acids as well as ethanol concentrations were modified. A hybrid model was proposed to consider the effect of gene deletion on the metabolism of E. coli. The model parameters were estimated by the application of a least mean square method based on the instrument variable technique. To evaluate the parametric identifier method, a set of robust exact differentiators, based on the super-twisting algorithm, was implemented. The hybrid model was successfully characterized by the parameters obtained from experimental information of E. coli MG1655. The significant difference between parameters obtained with wild-type strain and the modified (with deleted genes) justifies the application of the parametric identification algorithm. This characterization can be used to optimize the production of different byproducts of commercial interest.