• Title of 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

  • Author/Authors

    Giordano، نويسنده , , Pablo C. and Martيnez، نويسنده , , Hugo D. and Iglesias، نويسنده , , Alberto A. and Beccaria، نويسنده , , Alejandro J. and Goicoechea، نويسنده , , Héctor C.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2010
  • Pages
    8
  • From page
    7537
  • To page
    7544
  • Abstract
    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 3.50 g 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 (YP/X) overcomes this disadvantage.
  • Keywords
    Artificial neural networks , Response surface methodology , Byproduct glycerol , Escherichia coli , Recombinant protein
  • Journal title
    Bioresource Technology
  • Serial Year
    2010
  • Journal title
    Bioresource Technology
  • Record number

    1921787