Statistical and neural network modeling of β-glucanase production by Streptomyces albogriseolus (PQ002238), and immobilization on chitosan-coated magnetic microparticles - Nourhan H. Elshami; Ghadir S. El‑Housseiny; Mahmoud A. Yassien; Nadia A. Hassouna (Bioresources and Bioprocessing)
Abstract β-Glucanases are a series of glycoside hydrolases (GHs) that are of special interest for various medical and biotechnological applications. Numerous β-glucanases were produced by different types of microorganisms. Particularly, bacterial β-glucanases have the privilege of being stable, easily produced, and suitable for large-scale production. This study aimed for finding potent β-glucanase producing bacterial strains and optimizing its production. Soil samples from Egyptian governorates were screened for such strains, and 96 isolates were collected. The β-glucanase activity was qualitatively assessed and quantitatively measured using 3,5-dinitrosalicylic acid (DNS) method. The highest β-glucanase producing strain (0.74 U/ml) was identified as Streptomyces albogriseolus S13-1. The optimum incubation period and temperature, determined one-variable at a time, were estimated as 4 d and 45 ͦ C, respectively. Similarly, yeast β-glucan and beef extract were selected as the best carbon and nitrogen sources, with enzymatic activities of 0.74 and 1.12 U/ml, respectively. Other fermentation conditions were optimized through response surface methodology (RSM); D-optimal design (DOD) with a total of 28 runs. The maximum experimental β-glucanase activity (1.3 U/ml) was obtained with pH 6.5, inoculum volume of 0.5% v/v, agitation speed of 100 rpm, carbon concentration of 1% w/v, and nitrogen concentration of 0.11% w/v. This was 1.76-fold higher compared to unoptimized conditions. Using the same experimental matrix, an artificial neural network (ANN) was built to predict β-glucanase production by the isolated strain. Predicted β-glucanase levels by RSM and ANN were 1.79 and 1.32 U/ml, respectively. Both models slightly over-estimated production levels, but ANN showed higher predictivity and better performance metrics. The enzyme was partially purified through acetone precipitation, characterized, and immobilized on chitosan-coated iron oxide microparticles. The optimal pH and temperature for enzyme activity were 5 and 50 °C, respectively. The immobilized enzyme showed superior characters such as higher stability at temperatures 50, 60, and 70 °C compared to the free enzyme, and satisfactory reusability, losing only 30% of activity after 6 cycles of reuse. Graphical Abstract