DETERMINING METABOLIC SENSITIVITY COEFFICIENTS DIRECTLY FROM EXPERIMENTAL-DATA

The application of metabolic control theory (MCT), or other methods of determining metabolic sensitivity to the rates of specific cellular processes, such as enzymatic reactions, requires knowledge of the elasticity coefficients (system partial derivatives) for the processes under study. Although rate equations are available in the literature for some enzymatic reactions, there are many reactions and processes for which this is not the case. Although one could perform the experiments necessary to determine the rate equations for a given system, these equations are, in fact, not required for the calculation of sensitivities-only the elasticities (the derivatives) are needed. A more direct and efficient approach would be to compute elasticities directly from experimental data. Errors can arise in such an approach, however, because data is invariably corrupted by noise and the linear regression used in such a calculation may be quite sensitive to this noise. Error analysis and alternative regression techniques are presented which not only allow one to eliminate data components with excessive noise, but also provide guidance as to what additional data may be required for accurate sensitivity analysis. This information indicates which measurements require more accuracy and what additional experiments should be conducted to reduce errors in calculated metabolic sensitivity coefficients.