Response surface modeling and optimization of media nutrients for enhanced production of y -linolenic Acid in the moss physcomitrella patens using response surface methodology

Abstract

The objective of this study is to obtain a model that maximize production of γ-linolenic acid (GLA) by the moss Physcomitrella patens, employing response surface methodology (RSM). The RSM with a three-variables (sucrose, potassium nitrate and glutamate concentrations) and five-level (-2, -1, 0, 1 and 2) central composite design (CCD) including 20 experimental runs was employed to optimize the medium composition. Results showed that the experimental data could be appropriately fitted into a second-order polynomial model with a coefficient of determination (R2) more than 0 .9 5 for GLA production. Analysis of variance (ANOVA) revealed that the model was highly significant (p<0.0001) and the effects of the sucrose (20-100 g/L) and glutamate (0.5-2.5 g/L) concentrations on GLA production were significant (p<0.05). The GLA production with the optimized culture medium (sucrose concentration of 62.92 g/L, potassium nitrate of 0.80 g/L and glutamate concentration of 1 .4 2 g/L) by RSM increased 4.61 folds when compared with the standard BCD medium. This experimental value (16.37 mg GLA/L) fit well with the predicted values (16.20 mg GLA/L).