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Efficient Sporulation of Saccharomyces cerevisiae in a 96 Multiwell Format
Published on: September 17, 2016
Modeling and optimization of sporulation by Bacillus licheniformis BF-002 based on dynamics and recurrent neural
Jian Ding1, Bo Wang1, Qingyuan Liu2
1The Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, 214122 Wuxi, China.
Abstract:
Bacillus licheniformis is widely utilized in disease prevention and environmental remediation. Spore quantity is a critical factor in determining the quality of microbiological agents containing vegetative cells. To improve the understanding of Bacillus licheniformis BF-002 strain culture, a hybrid model integrating traditional dynamic modeling and recurrent neural network was developed. This model enabled the optimization of carbon/nitrogen source feeding rates, pH, temperature and agitation speed using genetic algorithms. Carbon and nitrogen source consumption in the optimal duplicate batches showed no significant difference compared to the control batch. However, the spore quantity in the broth increased by 16.2% and 35.2% in the respective duplicate batches. Overall, the hybrid model outperformed the traditional dynamic model in accurately tracking the cultivation dynamics of Bacillus licheniformis, leading to increased spore production when used for optimizing cultivation conditions.
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