pH-adaptive evolution of glutamate decarboxylase enables gamma-aminobutyric acid biosynthesis without pH control

The strict pH-dependent catalytic activity of glutamate decarboxylase (GAD) necessitates substantial acid consumption during γ-aminobutyric acid (GABA) biosynthesis, increasing costs and environmental impact. To overcome this limitation, we engineered glutamate decarboxylase from Escherichia coli (EcGadB) for enhanced activity at neutral pH. Using constant pH molecular dynamics (CpHMD) simulations, we targeted the pH-sensitive γ-carboxyl-binding loop (γ-CBL). Through three rounds of Adaptive Iterative Evolution (AIE) guided by a GABA biosensor, mutant M3 (Y51L/A56P/D68N/D69T) was obtained, which exhibited a 43.5-fold enhancement in catalytic efficiency (k_cat/K_m) at pH 7.5. Gaussian-accelerated MD simulations indicated that M3 stabilizes catalytic conformations of γ-CBL, decoupling its activity from acidic conditions. By further design, mutant M4 (M3-Q348D/M431K) with significantly improved thermostability was obtained. M4 was applied to three pH-control-free catalytic systems: achieving 360 g/L GABA in enzymatic catalysis (50 °C, 8 h), 219 g/L in whole-cell biocatalysis, and 60 g/L (1.71 g/L/h space–time yield) in high-cell-density fermentation. This study establishes an integrated computational/directed evolution loop engineering paradigm, enabling efficient, sustainable, and economically viable enzymatic GABA production by eliminating pH control requirements and enhancing process robustness.