Efficient production of poly-γ-glutamic acid using computational fluid dynamics simulations by Bacillus velezensis for frozen dough bread making

Abstract

This study aimed to evaluate poly-γ-glutamic acid (γ-PGA) production by the glutamic-dependent strain Bacillus velezensis CAU263 through fed-batch fermentation in a 5-L fermenter. A remarkable γ-PGA yield of 60.4 g/L with a conversion rate of 0.97 g/g (γ-PGA/L‑sodium glutamate) was achieved. To further enhance the γ-PGA yield, computational fluid dynamics (CFD) simulations were performed to optimize impeller combinations. With the adoption of six-semicircular blade Rushton turbine and four-skewed wide blade impellers (with a 20 % increase in impeller diameter), B. velezensis CAU263 produced a staggering 80.7 g/L of γ-PGA with a conversion rate of 1.29 g/g (γ-PGA/L‑sodium glutamate). Furthermore, γ-PGA greatly improved the fermentation properties of frozen dough, yielding a 21.3 % increase in the specific volume of frozen dough bread and a remarkable 38.3 % reduction in hardness. Therefore, an efficient strategy for B. velezensis producing γ-PGA was provided, and the γ-PGA has tremendous potential as a cryoprotectant agent in the baking industry.

Keywords

• Poly-γ-glutamic acid
• Bacillus velezensis
• Fed-batch fermentation
• Computational fluid dynamics
• Frozen dough
• Bread