Computational modeling of culture media for enhanced production of fibrinolytic enzyme from marine bacterium Fictibacillus sp. strain SKA27 and in vitro evaluation of fibrinolytic activity.

Abstract

The present study reports the optimized production and purification of an extremely active fibrinolytic enzyme from newly isolated marine bacterium Fictibacillus sp. strain SKA27, with a specific activity of 125,107.85U/mg and an apparent molecular weight of 28kDa on SDS-PAGE. Wheat bran extract used for submerged production proved to be highly beneficial and enhanced fibrinolytic enzyme production when combined with yeast extract and CaCl2. Optimization of culture media by response surface methodology (RSM) resulted in high root mean square error (RMSE), which led to the training of a back propagation multilayer artificial neural network (ANN) with 3-5-1 topology for better prediction quality. The prediction and optimization capabilities of regression and ANN were critically examined and ANN displayed higher proficiency with R 2 of 0.99 and RMSE of 2.0 compared to 0.98 R 2 and 48.9 RMSE of the regression model. An adept ANN linked genetic algorithm (GA) optimized the medium components to achieve 1.8-fold higher enzyme production (4175.41U/mL). Further, a new and improved in vitro qualitative analysis displayed high specificity of purified enzyme to fibrin.