Characterization and statistical optimization of γ-PGA produced by Bacillus megaterium UP47 isolated from Pentaclethra macrophylla

Abstract

BACKGROUND: Gamma-polyglutamic acid (γ-PGA) is a microbially produced non-toxic peptide biopolymer which is gaining grounds in many biotechnological fields and has a wide range of applications. OBJECTIVES: In this study, the characteristics of γ-PGA produced by Bacillus megaterium isolated from an oil seed were determined, while the nutritional requirements of the bacterium were optimized using a predictive 15 factor-16 run Plackett-Burman experimental design. MATERIAL AND METHODS: The main effect of each factor, the interaction and quadratic effects of the factors on optimized production were determined from Box-Benkhen model using Dell Statistica v. 12 and 13 software. Bacillus megaterium UP47 produced the highest γ-PGA (16.33 g/L) out of 56 spore-forming Bacillus strains isolated from soil, water and fermented food samples. RESULTS: Hydrolysates of the produced γ-PGA had a retention factor which corresponded to the L-glutamic acid standard (retention factor (rf) 0.35), while high-definition fourier transform infrared (FT-IR) spectroscopic imaging showed characteristic peaks representative of the active bonds present in γ-PGA. The γ-PGA at a concentration as low as 50 mg/100 mL exerted antimicrobial inhibitions against test pathogens. A 2.00 w/v γ-PGA solution had 11 mm and 13 mm inhibition zones against Staphylococcus aureus and Shigella dysenteriae, respectively. A second order polynomial equation for prediction of γ-PGA was derived as: γPGA yield = 3316.061 - 449.708A + 9.036A2 - 139.813B + 3.095B2 - 7.699C - 0.164C2 + 13.116AB - 0.087AB2 - 0.248A2B + 3.781AC - 0.076A2C - 0.394BC. It showed an increase in γ-PGA yield with increasing L-glutamic acid and biotin, but a decrease with yeast extract. CONCLUSIONS: Bacillus megaterium UP47 had a maximum γ-PGA yield of 54 g/L and 62 g/L, respectively, from the Plackett-Burman and Box-Benkhen design, thereby resulting in an appreciable increase in polymer yield after the optimization process with a 95% confidence level.