Statistical optimization of alkaline protease production from newly isolated Pseudomonas species MTCC 16017

Abstract

The present study was investigated to optimize the production parameters using statistical method of the industrially important enzyme alkaline protease from newly isolated strain Pseudomonas putida from soil microorganisms. Methodology and results: Among 50 isolates of extensive screening two highly productive strains were selected. One among after biochemical characterization both laboratory level and by IMTECH Chandigarh was confirmed as P. putida. Submerged fermentation was carried out and statistical optimization methods Plackett and Burman and RSM were used to optimize the production parameters. Conclusion, significance and impact of study: Among the two selected strains out of 50 isolates, P. putida was identified as the one of the major protease producer. In this study eleven parameters were selected for the fractional factorial design (Plackett and Burman). Four significant parameters including time, carbon source, nitrogen source and salt showed significant impact on the alkaline protease production. During the study an increase in the alkaline protease activity from 4.659 U/mL to 7.396 U/mL was observed. Based on the above data more complex designs, such as Box Wilson design to study the impact of individual significant variable on the enzyme production as well as interactive effects among these significant variables were carried out. The interactive effect of the most influential parameters resulted in increase in enzyme activity from 7.246 up to 10.818 U/mL in 60 h. Analysis of variance showed the adequacy of the model and verification experiments confirmed its validity.