RSM and ANN driven optimization and thermodynamic characterization of CMCase and FPase for enhanced biomass degradation from locally isolated Bacillus mycoides strain 6i in submerged fermentation
Abstract
Cellulases are industriallysignificant enzymes that play a vital role in the field of bioprocessing technology. This research focused mainly on theisolation, identification, and phylogenetic analysis of a newly identified Bacillus strains using the16S rRNA sequencing technique. Likewise, production of cellulase from Bacillus mycoides strain 6i was statistically optimized by using mango kernels in submerged fermentation using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). Both RSM and ANN were used to successfully optimize CMCase and FPase. Plackett-Burmandesign (PBD)wasadopted for screening themost significant factors (X5 = peptone, X6 = NaCl, and X7 = (NH 4 ) 2 SO 4 )and Central Composite Design (CCD) wasemployed for optimization of thetarget enzyme using Bacillus mycoides 6i strain. Maximum CMCaseproduction (118.08 IU/mL/min) was recorded at 24 h incubation, 1.25% peptone, 1% NaCl, and0.5% (NH 4 )2SO 4 . Highest FPaseproduction(118.0003 IU/mL/min)was recorded at 24 h incubation, 0.09% peptone, 0.65% NaCl, and 0.3% (NH 4 ) 2 SO 4 .CMCase displayed maximum enzyme activity at 70 °C and pH 7. FPasedisplayed maximum enzyme activity at 70 °C and pH 5. Enzymecharacterization including temperature, pH, metal ions, solvents,surfactants, and detergent analysis wasalso performed. Cellulases showed activation energy (Ea) of 33.20 and 11.33 kJ/mol,enthalpy change (∆H) of 44.0 and 11.4 kJ/mol,and entropy (∆S) of 49.84 and 42.21 J mol⁻ 1 K⁻ 1 for CMCase and FPase, respectively.R 2 values for CMCase and FPase were 94.55% and 94.65%, respectively, ascalculated by RSM analysis.R 2 values for CMCase and FPase were 95.794% and 95.241%, respectively, as calculated by ANN analysis. ANN better captured the nonlinearrelationships between variables than RSM, asindicated by the higher R 2 values. This study provides insights intoproduction, optimization, and characterization of cellulose-degradingenzymes from newly identified Bacillus strains.