RESULTS: The production medium was first optimized using a statistical optimization approach to increase pectinase production. A maximal enzyme concentration of 76.35 U/mL (a 2.8-fold increase compared with the initial medium) was produced in a medium composed of (g/L): pectin, 32.22; (NH4)2SO4, 4.33; K2HPO4, 1.36; MgSO4.5H2O, 0.05; KCl, 0.05; and FeSO4.5H2O, 0.10. The cultivations were then carried out in a 16-L stirred tank bioreactor in both batch and fed-batch modes to improve enzyme production, which is an important step for bioprocess industrialization. Controlling the pH at 5.5 during cultivation yielded a pectinase production of 109.63 U/mL, which was about 10% higher than the uncontrolled pH culture. Furthermore, fed-batch cultivation using sucrose as a feeding substrate with a rate of 2 g/L/h increased the enzyme production up to 450 U/mL after 126 h.
CONCLUSIONS: Statistical medium optimization improved volumetric pectinase productivity by about 2.8 folds. Scaling-up the production process in 16-L semi-industrial stirred tank bioreactor under controlled pH further enhanced pectinase production by about 4-folds. Finally, bioreactor fed-batch cultivation using constant carbon source feeding increased maximal volumetric enzyme production by about 16.5-folds from the initial starting conditions.
RESULTS: Here, we describe an automated screen, to enable high-throughput optimisation of 12 nutrients for microalgae production. Its miniaturised 1,728 multiwell format allows multiple microalgae strains to be simultaneously screened using a two-step process. Step 1 optimises the primary elements nitrogen and phosphorous. Step 2 uses Box-Behnken analysis to define the highest growth rates within the large multidimensional space tested (Ca, Mg, Fe, Mn, Zn, Cu, B, Se, V, Si) at three levels (-1, 0, 1). The highest specific growth rates and maximum OD750 values provide a measure for continuous and batch culture.
CONCLUSION: The screen identified the main nutrient effects on growth, pairwise nutrient interactions (for example, Ca-Mg) and the best production conditions of the sampled statistical space providing the basis for a targeted full factorial screen to assist with optimisation of algae production.
RESULTS: Natamycin production was investigated under the effect of different initial glucose concentrations. Maximal antibiotic production (1.58 ± 0.032 g/L) was achieved at 20 g/L glucose. Under glucose limitation, natamycin production was retarded and the produced antibiotic was degraded. Higher glucose concentrations resulted in carbon catabolite repression. Secondly, intermittent feeding of glucose improved natamycin production due to overcoming glucose catabolite regulation, and moreover it was superior to glucose-beef mixture feeding, which overcomes catabolite regulation, but increased cell growth on the expense of natamycin production. Finally, the process was optimized in 7.5 L stirred tank bioreactor under batch and fed-batch conditions. Continuous glucose feeding for 30 h increased volumetric natamycin production by about 1.6- and 1.72-folds in than the batch cultivation in bioreactor and shake-flasks, respectively.
CONCLUSIONS: Glucose is a crucial substrate that significantly affects the production of natamycin, and its slow feeding is recommended to alleviate the effects of carbon catabolite regulation as well as to prevent product degradation under carbon source limitation. Cultivation in bioreactor under glucose feeding increased maximal volumetric enzyme production by about 72% from the initial starting conditions.