NDLI: Fed-batch optimization of recombinant α-amylase production by Bacillus subtilis using a modified Markov chain Monte Carlo technique

Content Provider	Springer Nature Link
Author	Skolpap, Wanwisa Nuchprayoon, Somboon Scharer, Je M. Grisdanurak, Nurak Douglas, Peter L. Moo Young, Murray
Copyright Year	2008
Abstract	A modified Markov Chain Monte Carlo (MCMC) searching procedure was developed to search for an optimal set of decision variables and optimal feed rate trajectories for recombinant α-amylase expression by Bacillus subtilis ATCC 6051a. The bacterium also synthesizes proteases as undesirable products in fed-batch culture that need to be minimized. To maximize α-amylase productivity, a 14th-order fed-batch model was optimized by integrating Pontryagin’s maximum principle with the Luedeking-Piret equation. The number of iterations and simulations of the proposed searching procedure were statistically examined for accuracy and acceptability of the results. It can be concluded that the proposed searching procedure increased the parameter selection opportunity near the tail ends of redefined triangular distribution. By applying a modified MCMC searching procedure with 1,500 iterations, the predicted α-amylase productivity was improved by 18% in comparison with near-optimum experimental results. This productivity was 3.5% higher than predicted by conventional MCMC optimization.
Starting Page	646
Ending Page	655
Page Count	10
File Format	PDF
ISSN	02561115
Journal	Korean Journal of Chemical Engineering
Volume Number	25
Issue Number	4
e-ISSN	19757220
Language	English
Publisher	Springer US
Publisher Date	2008-09-16
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bacillus subtilis Fed-batch Culture Nonlinear Optimization Problem Markov Chain Monte Carlo Biotechnology Materials Science Catalysis Industrial Chemistry/Chemical Engineering
Content Type	Text
Resource Type	Article
Subject	Chemistry Chemical Engineering

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