Multi-enzyme producing lignocellulolytic bacteria from biogas slurry: molecular identification and optimization of...

Biogas slurry is a residue left after anaerobic digestion that is commonly applied as an organic fertilizer; however, its microbial potential for enzyme production has received comparatively limited attention. In the present study, biogas slurry was examined as a source of lignocellulolytic bacteria to evaluate the multi-enzyme producing capabilities for applications in biomass degradation and waste valorisation. Using culture-dependent techniques, 31 bacterial isolates were obtained and characterized based on morphological and biochemical properties. The isolates were initially screened for cellulase, xylanase, amylase and laccase activities using substrate-specific agar plate assays, and selected isolates were further evaluated for quantitative enzyme production. Considerable variation in enzyme activity was observed among the isolates, with maximum activities of 1.374 ± 0.059 U/ml for carboxymethyl cellulase, 0.484 ± 0.006 U/ml for filter paperase, 0.649 ± 0.017 U/ml for β-glucosidase, 2.060 ± 0.066 U/ml for amylase and 1.241 ± 0.031 U/ml for xylanase. Molecular identification based on 16 S rRNA gene sequencing indicated that the predominant enzyme producing isolates belonged to Bacillus subtilis, Bacillus albus, Serratia nematodiphila, and Pseudomonas aeruginosa, which was validated through phylogenetic analysis. Based on enzyme production, Bacillus subtilis BCA-1 was selected for biomass degradation and optimization studies using alkali-treated corn cob under solid-state fermentation. Maximum cellulase activity (3.830 ± 0.102 U/ml) was observed at pH 7, 45 °C, and 72 h, while xylanase (2.033 ± 0.058 U/ml) and β-glucosidase (3.290 ± 0.095 U/ml) activities were highest at pH 6, 45 °C, and 72 h. The results demonstrated that biogas slurry contains functionally diverse lignocellulolytic bacteria capable of coordinated multi-enzyme production. Enhanced enzyme production by Bacillus subtilis BCA-1 under optimized conditions indicates substrate-induced enzyme expression and supports its potential application in lignocellulosic biomass conversion.