Two-stage fermentation process for enhanced mannitol production using Candida magnoliae mutant R9.

Mutants of Candida magnoliae NCIM 3470 were generated by treatment of ultra-violet radiations, ethyl methyl sulphonate and N-methyl-N'-nitro-N-nitrosoguanidine. Mutants with higher reductase activity were screened by means of 2,3,5-triphenyl tetrazolium chloride agar plate assay. Among the screened mutants, the mutant R9 produced maximum mannitol (i.e. 46 g l(-1)) in liquid fermentation medium containing 250 g l(-1) glucose and hence was selected for further experiments. Preliminary optimization studies were carried out on shake-flask level which increased the mannitol production to 60 g l(-1) in liquid fermentation medium containing 300 g l(-1) glucose. A two-stage fermentation process comprising of growth phase and production phase was employed. During the growth phase, glucose was supplemented and aerobic conditions were maintained. Thereafter, the production phase was initiated by supplementing fructose and switching to anaerobic conditions by discontinuing aeration and decreasing the speed of agitation. The strategy of two-stage fermentation significantly enhanced the production of mannitol up to 240 g l(-1), which is the highest among all fermentative production processes and corresponds to 81 % yield and 4 g l(-1 )h(-1) productivity without formation of any by-product.

Media optimization for biosurfactant production by Rhodococcus erythropolis MTCC 2794: artificial intelligence versus a statistical approach.

This paper entails a comprehensive study on production of a biosurfactant from Rhodococcus erythropolis MTCC 2794. Two optimization techniques--(1) artificial neural network (ANN) coupled with genetic algorithm (GA) and (2) response surface methodology (RSM)--were used for media optimization in order to enhance the biosurfactant yield by Rhodococcus erythropolis MTCC 2794. ANN and RSM models were developed, incorporating the quantity of four medium components (sucrose, yeast extract, meat peptone, and toluene) as independent input variables and biosurfactant yield [calculated in terms of percent emulsification index (% EI(24))] as output variable. ANN-GA and RSM were compared for their predictive and generalization ability using a separate data set of 16 experiments, for which the average quadratic errors were approximately 3 and approximately 6%, respectively. ANN-GA was found to be more accurate and consistent in predicting optimized conditions and maximum yield than RSM. For the ANN-GA model, the values of correlation coefficient and average quadratic error were approximately 0.99 and approximately 3%, respectively. It was also shown that ANN-based models could be used accurately for sensitivity analysis. ANN-GA-optimized media gave about a 3.5-fold enhancement in biosurfactant yield.

Enhanced production of amidase from Rhodococcus erythropolis MTCC 1526 by medium optimisation using a statistical experimental design.

In the present work, statistical experimental methodology was used to enhance the production of amidase from Rhodococcus erythropolis MTCC 1526. R. erythropolis MTCC 1526 was selected through screening of seven strains of Rhodococcus species. The Placket-Burman screening experiments suggested that sorbitol as carbon source, yeast extract and meat peptone as nitrogen sources, and acetamide as amidase inducer are the most influential media components. The concentrations of these four media components were optimised using a face-centred design of response surface methodology (RSM). The optimum medium composition for amidase production was found to contain sorbitol (5 g/L), yeast extract (4 g/L), meat peptone (2.5 g/L), and acetamide (12.25 mM). Amidase activities before and after optimisation were 157.85 units/g dry cells and 1,086.57 units/g dry cells, respectively. Thus, use of RSM increased production of amidase from R. erythropolis MTCC 1526 by 6.88-fold.

Use of response surface optimization for the production of biosurfactant from Rhodococcus spp. MTCC 2574.

The production of biosurfactant from Rhodococcus spp. MTCC 2574 was effectively enhanced by response surface methodology (RSM). Rhodococcus spp. MTCC 2574 was selected through screening of seven different Rhodococcus strains. The preliminary screening experiments (one-factor at a time) suggested that carbon source: mannitol, nitrogen source: yeast extract and meat peptone and inducer: n-hexadecane are the critical medium components. The concentrations of these four media components were optimized by using central composite rotatable design (CCRD) of RSM. The adequately high R2 value (0.947) and F score 19.11 indicated the statistical significance of the model. The optimum medium composition for biosurfactant production was found to contain mannitol (1.6 g/L), yeast extract (6.92 g/L), meat peptone (19.65 g/L), n-hexadecane (63.8 g/L). The crude biosurfactant was obtained from methyl tert-butyl ether extraction. The yield of biosurfactant before and after optimization was 3.2 g/L of and 10.9 g/L, respectively. Thus, RSM has increased the yield of biosurfactant to 3.4-fold. The crude biosurfactant decreased the surface tension of water from 72 mN/m to 30.8 mN/m (at 120 mg L(-1)) and achieved a critical micelle concentration (CMC) value of 120 mg L(-1).

Immobilization of Candida rugosa lipase on poly(allyl glycidyl ether-co-ethylene glycol dimethacrylate) macroporous polymer particles.

Macroporous polymer particles containing surface epoxy groups were synthesized for immobilization of Candida rugosa lipase (CRL). The effect of incorporation of two different sets of monomers [allyl glycidyl ether (AGE) and glycidyl methacrylate (GMA)] and the effect of crosslinking density on immobilization of lipase were studied. AGE-co-EGDM polymers gave higher binding and expression of lipase than GMA-co-EGDM polymers. Optimization of immobilization parameters was done with respect to immobilization time and enzyme loading. Amongst AGE-co-EGDM polymer series, AGE-150 polymer found to give maximum lipase activity yield and therefore evaluated for temperature, pH and storage stability. Under optimum conditions, AGE-150 polymer gave 78.40% of activity yield. Immobilized lipase on AGE-150 showed a broader pH, higher temperature and excellent storage stability.

Use of insoluble yeast beta-glucan as a support for immobilization of Candida rugosa lipase.

In the present study, insoluble yeast beta-glucan (IYG) has been explored as a support matrix for enzyme immobilization. IYG contains mainly beta-(1-3) linkages along with some intra- or inter-molecular branches of beta-(1-6) linkages with large number of free hydroxyl groups. Epichlorohydrin was used to convert these free hydroxyl groups into activated epoxy groups that are capable of forming covalent linkages with various groups of enzyme molecule. The epoxy-activated IYG was evaluated for immobilization of Candida rugosa lipase (CRL). Post-immobilization treatment of 5% glutaraldehyde was given in order to achieve stable and irreversible binding of enzyme on the support. The resultant biocatalytic IYG support expressed lipase activity of 8136.7 U/g and 59.6% activity yield. There was 51.05% retention of synthetic activity after six repeated esterification cycles, indicating its stability and reusability in non-aqueous medium. Moreover, the immobilized lipase gave the storage half-life of about 285 days (at 4 degrees C).