Identification of GABA producing strains from sourdoughs and optimization of GABA production by response surface-integrated particle swarm approach

Abstract

Lactic Acid Bacteria (LAB) strains were isolated from sourdough samples collected from five provinces of T & uuml;rkiye and the Cyprus region. The gamma-aminobutyric acid (GABA) production ability of these LAB strains with (+) gad gene regions was evaluated. Response Surface Method (RSM) and Particle Swarm Optimization (PSO) techniques were used together to optimize the GABA environment of Levilactobacillus brevis SD48 strain with the highest GABA production. Optimization of fermentation conditions for GABA production of Levilactobacillus brevis SD48 strain was designed with Box-Behnken design. Optimization parameters tested were pH, temperature, time and monosodium glutamate (MSG) concentration. Fermentation time (24, 48, 72 hours), pH values (4.5, 5.75 and 7.0), temperature (30, 35 and 40 degrees C), MSG concentration (50, 225, 400 mM) were taken. It was seen that the best process parameters that allow maximum GABA yield should be temperature 30 degrees C, MSG concentration 130.71 mM, pH 4.74 and time 72 hour. According to the results, it can be thought that microbial production of GABA is both cheap and the optimized conditions we determined will play an important role in the production of GABA-rich fermented foods.