An extracellular alkaline lipase from Pseudomonas aeruginosa mutant has been purified to homogeneity using acetone precipitation followed by anion exchange and gel filtration chromatography and resulted in 27-fold purification with 19.6% final recovery. SDS-PAGE study suggested that the purified lipase has an apparent molecular mass of 67 kDa. The optimum temperature and pH for the purified lipase were 45°C and 8.0, respectively. The enzyme showed considerable stability in pH range of 7.0-11.0 and temperature range 35-55 °C. The metal ions Ca2+, Mg2+ and Na+ tend to increase the enzyme activity, whereas, Fe2+ and Mn2+ ions resulted in discreet decrease in the activity. Divalent cations Ca+2 and Mg+2 seemed to protect the enzyme against thermal denaturation at high temperatures and in presence of Ca+2 (5 mM) the optimum temperature shifted from 45°C to 55°C. The purified lipase displayed significant stability in the presence of several hydrophilic and hydrophobic organic solvents (25%, v/v) up to 168 h. The pure enzyme preparation exhibited significant stability and compatibility with oxidizing agents and commercial detergents as it retained 40-70% of its original activities. The values of Km and Vmax for p-nitrophenyl palmitate (p-NPP) under optimal conditions were determined to be 2.0 mg.mL-1 and 5000 μg.mL-1.min-1, respectively.

Alkaline lipase production by mutant strain of Pseudomonas aeruginosa MTCC 10,055 was optimized in shake flask batch fermentation using response surface methodology. An empirical model was developed through Box-Behnken experimental design to describe the relationship among tested variables (pH, temperature, castor oil, starch and triton-X-100). The second-order quadratic model determined the optimum conditions as castor oil, 1.77 mL.L-1; starch, 15.0 g.L-1; triton-X-100, 0.93 mL.L-1; incubation temperature, 34.12 ºC and pH 8.1 resulting into maximum alkaline lipase production (3142.57 U.mL-1). The quadratic model was in satisfactory adjustment with the experimental data as evidenced by a high coefficient of determination (R²) value (0.9987). The RSM facilitated the analysis and interpretation of experimental data to ascertain the optimum conditions of the variables for the process and recognized the contribution of individual variables to assess the response under optimal conditions. Hence Box-Behnken approach could fruitfully be applied for process optimization.