4.8 Article

Application of response surface methodology and artificial neural networks for optimization of recombinant Oryza sativa non-symbiotic hemoglobin 1 production by Escherichia coli in medium containing byproduct glycerol

Journal

BIORESOURCE TECHNOLOGY
Volume 101, Issue 19, Pages 7537-7544

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.biortech.2010.05.001

Keywords

Artificial neural networks; Response surface methodology; Escherichia coli; Byproduct glycerol; Recombinant protein

Funding

  1. CONICET [PIP 112-200801-02988]
  2. ANPCyT [PICTO 559 05 Ndegrees 35124]
  3. Universidad Nacional del Litoral [CAI+D 2008-O, CAI+D 2009-R2]

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Production of recombinant Oryza sativa non-symbiotic hemoglobin 1 (OsHb1) by Escherichia coli was maximized in shake-flask cultures in media containing tryptone, yeast extract, sodium chloride and byproduct glycerol from biodiesel production. Response surface methodology (RSM) and artificial neural networks (ANNs), followed by multiple response optimization through a desirability function were applied to evaluate the amount of OsHb1 produced. The results obtained by the application of ANNs were more reliable since better statistical parameters were obtained. The optimal conditions were (g L-1), tryptone, 42.69; yeast extract, 20.11; sodium chloride, 17.77; and byproduct glycerol, 0.33. A maximum recombinant protein concentration of 3.50g L-1 and a minimum biomass concentration of 18.48 g L-1 were obtained under these conditions. Although the concentrations of tryptone, yeast extract and sodium chloride are relatively high, the increase in the yield with respect to biomass formed (Y-P/X) overcomes this disadvantage. (C) 2010 Elsevier Ltd. All rights reserved.

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