Fed-batch optimization of α-amylase and protease-producing Bacillus subtilis using Markov chain methods

A stoichiometry-based model for the fed-batch culture of the recombinant bacterium Bacillus subtilis ATCC 6051a, producing extracellular a-amylase as a desirable product and proteases as undesirable products, was developed and verified. The model was then used for optimizing the feeding schedule in fed-batch culture. To handle higher-order model equations (14 state variables), an optimization methodology for the dual-enzyme system is proposed by integrating Pontryagin's optimum principle with fermentation measurements. Markov chain Monte Carlo (MCMC) procedures were appropriate for model parameter and decision variable estimation by using a priori parameter distributions reflecting the experimental results. Using a simplified Metropolis-Hastings algorithm, the specific productivity of a-amylase was maximized and the optimum path was confirmed by experimentation. The optimization process predicted a further 14% improvement of a-amylase productivity that could not be realized because of the onset of sporulation. Among the decision variables, the switching time from batch to fed-batch operation (t(s)) was the most sensitive decision variable. (C) 2004 Wiley Periodicals, Inc.