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Optimization of the Biosynthesis Conditions of Daptomycin by the Biostatistical Methodology

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Interdisciplinary Sciences: Computational Life Sciences Aims and scope Submit manuscript


Response surface methodology (RSM) was employed to optimize medium components including oxygen vector of n-dodecane of a mutant strain GC-63 of Streptomyces roseosporus NRRL 11379. The two-level Plackett–Burman design (PB factorial design) with fourteen variables including oxygen vector was used to screen the most significant factors affecting antibiotic production. Then, the RSM based on center composite design was used to identify the optimum levels of the significant variables to generate optimal response. Glucose, soybean meal, asparagine and n-dodecane were screened to significantly influence the daptomycin production. The medium composition optimized with response surface methodology was (g/L): glucose, 9.46; soluble starch, 25; dextrin, 12.5; yeast extract, 12.5; soybean meal, 21.34; peptone, 25; casein, 5; asparagine, 2.68; K2SO4, 6; (NH4)2Fe(SO4)2, 2; MgSO4, 1; CaCO3, 5; MnCl2, 0.5; n-dodecane, 7.47 % (v/v). The maximum daptomycin concentration reached 979.36 mg/L which was nearly 2.2-fold higher compared to that in the basal medium, with predicted optimal concentrations in a 7.5-L fermentor.

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This work was supported by 21506048 and 51408396 from the National Natural Science Foundation of China. And the authors also wished to acknowledge the financial support provided by Excellent Talents Project of Henan University of Technology (2011BS037).

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Correspondence to Guanghai Yu.

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Yu, G., Wang, G. Optimization of the Biosynthesis Conditions of Daptomycin by the Biostatistical Methodology. Interdiscip Sci Comput Life Sci 9, 80–87 (2017).

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