Abstract
Background: The increasing antimicrobial resistance has led to a greater demand for alternative treatment options, which in turn has increased interest in naturally occurring biomolecules such as pyocyanin. Methods: In this study, a three-factor Box-Behnken Design (BBD)-based response surface methodology (RSM) was employed to optimize the effects of glycerol, peptone, and pH on pyocyanin production by Pseudomonas aeruginosa OG1. The antimicrobial efficacy of the optimized pyocyanin was subsequently evaluated in vitro against three Candida species and four clinically important bacterial pathogens using the disk diffusion method, with gentamicin and fluconazole used as positive controls. Results: The second-order polynomial model demonstrated excellent fit (F = 176.3, p < 0.0001) with a non-significant lack of fit, indicating adequate representation of the experimental data. The optimal conditions were determined to be glycerol at 1.11% (w/v), peptone at 17.86 g/L, and a pH of 7.27, yielding a predicted pyocyanin concentration of 25.92 mg/L. Antimicrobial testing revealed broad-spectrum, dose-dependent activity against all tested microorganisms. The highest efficacy was observed against Bacillus cereus (26.4 ± 1.3 mm at 40 µg/mL), followed by Candida glabrata (21.5 ± 1.6 mm), Klebsiella pneumoniae (17.6 ± 1.4 mm), Candida albicans (15.4 ± 1.8 mm), Candida parapsilosis (13.2 ± 1.9 mm), Proteus mirabilis (12.5 ± 1.3 mm), and MRSA Staphylococcus aureus (9.2 ± 1.1 mm). Conclusions: These findings demonstrate that BBD-based RSM is a robust approach for optimizing pyocyanin production and that pyocyanin represents a promising dose-dependent antimicrobial agent against susceptible pathogens.