Multilevel algorithms and evolutionary hybrid tools for enhanced production of arginine deiminase from Pseudomonas furukawaii RS3

Abstract In the present study a high arginine deiminase (ADI) yielding bacterium was isolated from soil samples of Haryana, India and identified as Pseudomonas furukawaii. The specific enzyme activity was optimized to 1.420 IU/ml by OFAT and further enhanced to 2.708 IU/ml (an increase of 90.7%) with the help of statistical parametric optimization approaches using GA-ANN and GA-ANFIS. The obtained value of the coefficient of correlation (R = 0.88) for ANN and epoch error (0.12) for ANFIS, indicates the prediction accuracy and strength of these data training models. ADI production was improved significantly in simple super broth media supplemented with 1.5% fructose and 1.75% arginine at pH 7 at 37 °C using multilevel algorithms and evolutionary hybrid tools. The native enzyme was partially purified (ten-fold) up to a specific enzyme activity of 29.559 IU/mg.