A novel fed-batch based strategy for enhancing cell-density and recombinant cyprosin B production in bioreactors.

Nowadays, the dairy industry is continuously looking for new and more efficient clotting enzymes to create innovative products. Cyprosin B is a plant aspartic protease characterized by clotting activity that was previously cloned in Saccharomyces cerevisiae BJ1991 strain. The production of recombinant cyprosin B by a batch and fed-batch culture was compared using glucose and galactose as carbon sources. The strategy for fed-batch cultivation involved two steps: in the first batch phase, the culture medium presented glucose 1 % (w/v) and galactose 0.5 % (w/v), while in the feed step the culture medium was constituted by 5 % (w/v) galactose with the aim to minimize the GAL7 promoter repression. Based on fed-batch, in comparison to batch growth, an increase in biomass (6.6-fold), protein concentration (59 %) and cyprosin B activity (91 %) was achieved. The recombinant cyprosin B was purified by a single hydrophobic chromatography, presenting a specific activity of 6 × 10(4) U·mg(-1), corresponding to a purification degree of 12.5-fold and a recovery yield of 16.4 %. The SDS-PAGE analysis showed that recovery procedure is suitable for achieving the purified recombinant cyprosin B. The results show that the recombinant cyprosin B production can be improved based on two distinct steps during the fed-batch, presenting that this strategy, associated with a simplified purification procedure, could be applied to large-scale production, constituting a new and efficient alternative for animal and fungal enzymes widely used in cheese making.

Use of chemometrics in the selection of a Saccharomyces cerevisiae expression system for recombinant cyprosin B production.

Two multivariate statistical methods, factor analysis (FA) and hierarchical cluster analysis (HCA), were applied to experimental data set to evaluate their usefulness in selecting the adequate expression system and optimal growth parameters for recombinant cyprosin B production. Using FA, the large data set was reduced to two factors representing 73.4% of variability. Factor 1, with 53.5% of variability, corresponds to recombinant cyprosin B expression and efficient secretion, while factor 2, accounting for 19.9% of variability, represents cell growth and physiological characteristics. FA and HCA allowed the establishment of correlations among different variables and the clusters obtained providing clear identification of the experimental parameters related to cyprosin B production, which results on more accurate scientific output and time saving when selection of an adequate expression system is concerned.