An on-line physiological state recognition system for the lysine fermentation process based on a metabolic reaction model.

A metabolic reaction model was developed for the lysine fermentation process by Corynebacterium glutamicum AJ-3462 to estimate the physiological state of the cells-that is, the growth and production activity, and the flux distribution of metabolites-from on-line measurable rates only. First, the extended Kalman filter was applied to eliminate noise in the measured rates. Then, using the metabolic reaction model, the lysine production rate and flux distribution were calculated. The estimation results allowed the physiological state of lysine production to be recognized, and an appropriate measure corresponding to the estimated state, such as intermittent addition of glucose and/or leucine, to be taken to maintain a high level of lysine productivity in batch culture. Finally, application of the recognition system enabled lysine to be produced from glucose at a higher yield than that from glucose- or leucine-limited exponential fed-batch cultures.