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Fed‐batch optimization of α‐amylase and protease‐producing Bacillus subtilis using Markov chain methods
Author(s) -
Skolpap Wanwisa,
Scharer J.M.,
Douglas P.L.,
MooYoung M.
Publication year - 2004
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.20079
Subject(s) - markov chain monte carlo , amylase , mathematical optimization , markov chain , bacillus subtilis , levansucrase , mathematics , computer science , biological system , monte carlo method , chemistry , statistics , biology , biochemistry , enzyme , bacteria , genetics
Abstract A stoichiometry‐based model for the fed‐batch culture of the recombinant bacterium Bacillus subtilis ATCC 6051a, producing extracellular α‐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 α‐amylase was maximized and the optimum path was confirmed by experimentation. The optimization process predicted a further 14% improvement of α‐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. © 2004 Wiley Periodicals, Inc.