Pilot scale production of recombinant hemicellulases and their saccharification potential

Synergistic saccharification ability of hemicellulases (endo-xylanase and β-xylosidase) was evaluated in this study for the bioethanol production from plant biomass. Endo-xylanase and β-xylosidase genes from Bacillus licheniformis were cloned and expressed in Escherichia coli BL21 (DE3). Maximum endo-xylanase production was obtained at 200 rpm agitation speed, air supply rate 2.0 vvm, 70% volume of the medium, 20% dissolved oxygen level and with 3% inoculum size. The optimal conditions for maximum production of recombinant β-xylosidase enzyme at pilot scale were 200 rpm agitation speed, 25% dissolved oxygen level, 2.5 vvm aeration rate, 70% volume of the medium with 2% inoculum size. Furthermore, the saccharification potential of these recombinant enzymes was checked for the production of xylose sugar by bioconversion of plant biomass by optimizing individually as well as synergistically by optimizing various parameters. Maximum saccharification (93%) of plant biomass was observed when both enzymes were used at a time with 8% sugarcane bagasse as a substrate and 200 units of each enzyme after incubation of 6 hr at 50 °C and 120 rpm. The results obtained in this study suggested these recombinant hemicellulases as potential candidates for the conversion of complex agricultural residues into simple sugars for ultimate use in the biofuel industry.

Optimization of process parameters and fermentation strategy for xylanase production in a stirred tank reactor using a mutant Aspergillus nidulans strain

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In batch fermentation, xylanase productivity was 313 U/mL/day.

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Maximum xylanase productivity was achieved at aeration of 2 vvm and 400 rpm.

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The optimum kLa for an efficient xylanase production was found to be 38.5 h⁻¹.

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Repeated batch fermentation increased xylanase productivity to 373 U/mL/day.

The present work studied the optimization of aeration rate, agitation rate and oxygen transfer and the use of various batch fermentation strategies for xylanase production from a recombinant Aspergillus nidulans strain in a 3 L stirred tank reactor. Maximum xylanase production of 1250 U/mL with productivity of 313 U/mL/day was obtained under an aeration rate of 2 vvm and an agitation rate of 400 rpm using batch fermentation. The optimum volumetric oxygen transfer coefficient (k_La) for efficient xylanase production was found to be 38.6 h⁻¹. Fed batch mode and repeated batch fermentation was also performed with k_La was 38.6 h⁻¹. Xylanase enzyme productivity increased to 327 with fed batch fermentation and 373 U/mL/day with repeated batch fermentation. Also, maximum xylanase activity increased to 1410 U/mL with fed batch fermentation and 1572 U/mL with repeated batch fermentation.

Growth profiling, kinetics and substrate utilization of low-cost dairy waste for production of β-cryptoxanthin by Kocuria marina DAGII

The dairy industry produces enormous amount of cheese whey containing the major milk nutrients, but this remains unutilized all over the globe. The present study investigates the production of β-cryptoxanthin (β-CRX) by Kocuria marina DAGII using cheese whey as substrate. Response surface methodology (RSM) and an artificial neural network (ANN) approach were implemented to obtain the maximum β-CRX yield. Significant factors, i.e. yeast extract, peptone, cheese whey and initial pH, were the input variables in both the optimizing studies, and β-CRX yield and biomass were taken as output variables. The ANN topology of 4-9-2 was found to be optimum when trained with a feed-forward back-propagation algorithm. Experimental values of β-CRX yield (17.14 mg l-1) and biomass (5.35 g l-1) were compared and ANN predicted values (16.99 mg l-1 and 5.33 g l-1, respectively) were found to be more accurate compared with RSM predicted values (16.95 mg l-1 and 5.23 g l-1, respectively). Detailed kinetic analysis of cellular growth, substrate consumption and product formation revealed that growth inhibition took place at substrate concentrations higher than 12% (v/v) of cheese whey. The Han and Levenspiel model was the best fitted substrate inhibition model that described the cell growth in cheese whey with an R2 and MSE of 0.9982% and 0.00477%, respectively. The potential importance of this study lies in the development, optimization and modelling of a suitable cheese whey supplemented medium for increased β-CRX production.