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Identification of unstructured model for subtilin production through Bacillus subtilis using hybrid genetic algorithm
R. Singh, S.S. Miriyala, , V.V. Kareenhalli,
Published in Elsevier Ltd
2017
Volume: 60
   
Pages: 1 - 12
Abstract
Subtilin production is favorable when Bacillus subtilis 168 is subjected to stress condition such as nutrient scarcity. A mathematical model underlying such growth process has immense applicability in determining the optimal operating conditions at industrial scale. We present this work with multiple objectives of a) selection of a substrate for creating the minimal nutrient media for B. subtilis thereby enhancing subtilin production, b) experimental study of the growth along with morphological characteristics of B. subtilis and product profile in nutrient scarcity condition and c) identification of an optimal unstructured model for subtilin production using a computational framework. First, we show that subtilin can be produced while B. subtilis is grown using galactose and B. subtilis undergoes morphological changes and takes filamentous shape. We then constructed a series of plausible models and used a hybrid method combining Genetic Algorithm and gradient based search methodologies, for model selection. The estimated kinetic parameters and the stoichiometric analysis indicate that the B. subtilis growth/death, product profile and respiratory mechanism undergo specific modifications in galactose as an adaptive response. Current study provides an inexpensive platform to produce subtilin and the predictive framework presented here has potential applications for large scale production of subtilin. © 2017 Elsevier Ltd
About the journal
JournalData powered by TypesetProcess Biochemistry
PublisherData powered by TypesetElsevier Ltd
ISSN13595113