Journal of Microbiology and Biotechnology

  • 제22권7호
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  • Pages.939-946
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  • 2012
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  • 1017-7825(pISSN)
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  • 1738-8872(eISSN)
한국미생물·생명공학회 (The Korean Society for Microbiology and Biotechnology)
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Enhanced Antibiotic Production by Streptomyces sindenensis Using Artificial Neural Networks Coupled with Genetic Algorithm and Nelder-Mead Downhill Simplex

  • Tripathi, C.K.M. (Division of Fermentation Technology, C.S.I.R., Central Drug Research Institute) ;
  • Khan, Mahvish (Department of Biotechnology, Integral University) ;
  • Praveen, Vandana (Division of Fermentation Technology, C.S.I.R., Central Drug Research Institute) ;
  • Khan, Saif (Department of Biotechnology, Integral University) ;
  • Srivastava, Akanksha (Division of Fermentation Technology, C.S.I.R., Central Drug Research Institute)
  • 투고 : 2011.09.14
  • 심사 : 2012.03.15
  • 발행 : 2012.07.28
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초록

Antibiotic 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 $95{\mu}g/ml$, which nearly doubled ($176{\mu}g/ml$) with the ANN-GA optimization. ANN-NMDS optimization was found to be more efficacious, and maximum antibiotic production ($197{\mu}g/ml$) was obtained by cultivating the cells with (g/l) fructose 2.7602, $MgSO_4$ 1.2369, $(NH_4)_2PO_4$ 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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