Nonlinear estimation of microbial and enzyme kinetic parameters from progress curve data

A computer program (BIOKINFIT) was developed to estimate microbial and enzy me kinetic parameters from progress curve data by nonlinear regression. BIO KINFIT overcomes the limitations associated with parameter estimation in no nlinear equations that are implicit in the dependent variable by numericall y approximating the substrate concentration in the integrated kinetic expre ssions. The simplex method was used to minimize the error between experimen tally observed and theoretically predicted substrate depletion data. The ro bustness of this approach was initially verified using synthetic substrate depletion data that were characterized by either simple or relative errors of known magnitude. Subsequently, previously published data from three diff erent experiments including the pyruvate kinase reaction, 2-chlorophenol bi odegradation, and glucose uptake by Penicillium chrysogenum were used to ve rify the utility of the present approach for kinetic parameter estimation. In all cases, experimental substrate depletion data were accurately describ ed by the theoretical curves and kinetic parameter estimates obtained in th is study using the simplex method were in close agreement with those report ed previously. BIOKINFIT, available free of charge on request, offers a con venient and robust method of analyzing progress curve data in implicit kine tic expressions.