Thermoalkalophilic polygalacturonase from a novel Glutamicibacter sp.: Bioprospecting, strain improvement, statistical optimization and applications.

The current research discusses a multidimensional bioprocess development, that includes bioprospecting, strain improvement, media optimisation, and applications of the extracted enzyme. A potent alkalophilic polygalacturonase (PG) producing bacterial strain was isolated and identified as a novel Glutamicibacter sp. Furthermore, strain improvement by UV and chemical mutagenesis not only improved the enzyme (PGmut) production but also enhanced its temperature optima from 37 °C to 50 °C. The use of solid substrate fermentation, followed bystatistical optimisation through PB and RSM, substantially increasedPGmut production. A 10-fold increase in enzyme production (632 U/gm) was observed when sugarcane bagasse with a pH of 10.5, 66.8 % moisture, and an inoculum size of 10.15 % was used. The model's accuracy was supported by p-value (p < 0.0001), and an R2 of 0.9940. A pilot-scale experiment, demonstrated ≈ 62,229 U/100 gm PG activity. Additionally, the enzyme's efficacy in demucilization of coffee beans, and bioscouring of jute fibre indicated that it is a valuable biocatalyst.

Statistical bioprocess optimization for enhanced production of a thermo alkalophilic polygalacturonase (PGase) from Pseudomonas sp. 13156349 using solid substrate fermentation (SSF).

In this study, a polygalacturonase (PGase) producing bacterial strain was isolated and identified as Pseudomonas sp. 13159349 from fruit market soils, and TLC analysis confirmed its pectinolytic activity. Additionally, SSF, Plackett-Burman design (PB), and response surface methodology (RSM) were used to optimize the production of this thermostable and alkalophilic PGase. Wheat bran demonstrated the highest activity (60.13 ± 3.39 U/gm) among the various agricultural wastes used as solid substrates. To further enhance the enzyme production, statistical optimization of media components was investigated using the PB design. Among the 11 variables tested, pH (p < 0.0001), inoculum size (p < 0.0001), incubation time (p < 0.0001), and temperature (p < 0.0041) were found to have a positive effect on the production. The interaction and concentration of the selected factors were examined by RSM, which demonstrated the optimal conditions for maximum production (315.65 U/gm) of the enzyme using wheat bran as the solid substrate were pH 10.5, 61-66 h of incubation, and 6-7.5% inoculum size. The model was highly significant, with a p-value of <0.0001, an F-value of 95.33, and a low CV of 2.31. The RSM model was validated by a laboratory-scale experiment showing 30600 ± 400.32 U/100 gm PGase activity. Thus, SSF and the statistical design of media components resulted in a significant 5.2-fold increase in PGase output solely by using agro waste and optimizing the physical parameters, making this a highly cost-effective bioprocess.