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Optimization of critical medium components for the maximal production of gentamicin by Micromonospora echinospora ATCC 15838 using response surface methodology

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Abstract

Optimization of the fermentation medium components for maximum gentamicin production by Micromonospora echinospora ATCC 15838 was carried out. Response surface methodology was applied to optimize the medium constituents. A 24full-factorial central composite design was chosen to explain the combined effects of the four medium constituents, viz. starch, soyabean meal, K2HPO4, and CoCl2 and to design a minimum number of experiments. A second order model was developed and fitted using least square method. The R 2 value of the model was 0.9723, which shows that model is best fit for the present studies. The results of analysis of variance and regression of a second order model showed that the linear effects of starch (p<0.001697) and CoCl2(p<7.99E-13), and cross product effects of starch and soyabean meal (p<0.029876) and soyabean meal and CoCl2 (p<0.008909) were more significant, suggesting that these were critical variables having the greatest effect on the production of gentamicin in the production medium. The optimized medium consisting of 9 g/L starch, 3 g/L soyabean meal, 0.9 g/L K2HPO4, and 0.01 g/L CoCL2 predicted 850 mg/L of gentamicin which was almost 110% higher than that of the unoptimized medium. The amounts of starch, soyabean meal, and K2HPO4 required were also reduced with RSM.

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Authors and Affiliations

  1. Microbiology Laboratory, Biochemical and Environmental Engineering Center, Indian Institute of Chemical Technology (CSIR), 500007, Hyderabad

    M. Himabindu, P. Ravichandra, K. Vishalakshi & Annapurna Jetty

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  1. M. Himabindu
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  2. P. Ravichandra
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  3. K. Vishalakshi
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  4. Annapurna Jetty
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Correspondence to Annapurna Jetty.

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Himabindu, M., Ravichandra, P., Vishalakshi, K. et al. Optimization of critical medium components for the maximal production of gentamicin by Micromonospora echinospora ATCC 15838 using response surface methodology. Appl Biochem Biotechnol 134, 143–154 (2006). https://doi.org/10.1385/ABAB:134:2:143

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  • DOI: https://doi.org/10.1385/ABAB:134:2:143

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