Journal of Microbiology and Biotechnology
The Korean Society for Microbiology and Biotechnology publishes the Journal of Microbiology and Biotechnology.
Journal of Microbiology and Biotechnology
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2012 ; 22(7): 939~946

AuthorC. K. M. Tripathi, Mahvish Khan, Vandana Praveen, Saif Khan, Akanksha Srivastava
AffiliationDivision of Fermentation Technology, C.S.I.R., Central Drug Research Institute, Lucknow 226001, India
TitleEnhanced Antibiotic Production by Streptomyces sindenensis Using Artificial Neural Networks Coupled with Genetic Algorithm and Nelder-Mead Downhill Simplex
PublicationInfo J. Microbiol. Biotechnol.2012 ; 22(7): 939~946
AbstractAntibiotic production with Streptomyces sindenensis MTCC 8122 was optimized under submerged fermentation conditions by artificial neural network (ANN) coupled with genetic algorithm (GA) and Nelder-Mead downhill simplex (NMDS). Feed forward back-propagation ANN was trained to establish the mathematical relationship among the medium components and length of incubation period for achieving maximum antibiotic yield. The optimization strategy involved growing the culture with varying concentrations of various medium components for different incubation periods. Under non-optimized condition, antibiotic production was found to be 95 μg/ml, which nearly doubled (176 μg/ml) with the ANN-GA optimization. ANN-NMDS optimization was found to be more efficacious, and maximum antibiotic production (197 μg/ml) was obtained by cultivating the cells with (g/l) fructose 2.7602, MgSO4 1.2369, (NH4)2PO4 0.2742, DL-threonine 3.069%, and soyabean meal 1.952%, for 9.8531 days of incubation, which was roughly 12% higher than the yield obtained by ANN coupled with GA under the same conditions.
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KeywordsStreptomyces sindenensis, Antibiotic, Artificial neural networks, Genetic algorithm, Nelder mead downhill simplex
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