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Improved Rifamycin B Production by Nocardia mediterranei MTCC 14 under Solid-State Fermentation through Process Optimization.

Vastrad BM, Neelagund SE, Iiger SR, Godbole AM, Kulkarni V - Biochem Res Int (2014)

Bottom Line: Optimum levels of the significant variables were decided by using a central composite design.At these optimum production parameters, the maximum yield of rifamycin B obtained experimentally (9.87 g/kgds dry sunflower oil cake) was found to be very close to its predicted value of 10.35 g/kgds dry sunflower oil cake.The mathematical model developed was found to fit greatly with the experimental data of rifamycin B production.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Biotechnology, S.E.T's College of Pharmacy, Dharwad, Karnataka 580002, India.

ABSTRACT
Optimization of various production parameters using response surface methodology (RSM) was performed to assess maximum yield of rifamycin B from Nocardia mediterranei MTCC 14. Plackett-Burman design test was applied to determine the significant effects of various production parameters such as glucose, maltose, ribose, galactose, beef extract, peanut meal, ammonium chloride, ammonium sulphate, barbital, pH, and moisture content on production of rifamycin B. Among the eleven variables tested, galactose, ribose, glucose, and pH were found to have significant effect on rifamycin B production. Optimum levels of the significant variables were decided by using a central composite design. The most appropriate condition for production of rifamycin B was found to be a single step production at galactose (8% w/w), ribose (3% w/w), glucose (9% w/w), and pH (7.0). At these optimum production parameters, the maximum yield of rifamycin B obtained experimentally (9.87 g/kgds dry sunflower oil cake) was found to be very close to its predicted value of 10.35 g/kgds dry sunflower oil cake. The mathematical model developed was found to fit greatly with the experimental data of rifamycin B production.

No MeSH data available.


Related in: MedlinePlus

Surface and contour plot for rifamycin B production at varying concentrations of X4, galactose (GA), and X3, ribose (RI).
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fig7: Surface and contour plot for rifamycin B production at varying concentrations of X4, galactose (GA), and X3, ribose (RI).

Mentions: Response surface methodology using central composite design was practical to optimize the levels of significant production parameters resulting from Plackett-Burman design experiments. Thirty experiments were carried out from the design and the experimental values are given in Table 5. All the experiments were carried out in duplicate; the mean value of rifamycin B yield was taken for statistical analysis. By applying multiple regression analysis on the experimental data, the following second-order polynomial equation was developed:(4)Rifamycin  B  (g/kgds) =+2306.89958−97.84583X4−244.48417X3  −14.31583X1−384.39167X10+6.26500X4X3  +1.50000X4X1−1.21000X4X10−2.11000X3X1  +20.15000X3X10−0.98000X1X10+4.42750X42  +9.07750X32+0.89750X12+22.55000X102.The effects of galactose (X4), ribose (X3), glucose (X1), and pH (X10) on rifamycin B production are reported in Table 7. Response surfaces for rifamycin B yield are shown in Figures 7–12, which give the surface and contour plots for the effect of galactose, ribose, glucose, and pH on the rifamycin B yield. Regression analysis of the experimental data (Table 7) showed that galactose and ribose had significant positive linear effects on rifamycin B yield, while glucose and pH had negative linear effect on rifamycin B yield. This was clear from the low P value obtained from the regression analysis. Among the four processes parameters, galactose was found to have the highest impact on rifamycin B yield as given by the highest linear coefficient (1.66) followed by ribose (0.23), while glucose (−0.40) and pH (−1.38) have negative linear effect. These production parameters also showed significant positive quadratic effects on rifamycin B yield indicating that rifamycin B production increased as the level of these factors increased and decreased as the level of these processes parameters decreased below certain values. Table also indicates that the interaction between ribose and pH and between galactose and ribose has significant effect on rifamycin B production and all other interactive variables are insignificant. Hence, only the term indicating interaction between ribose and pH and between galactose and ribose was included in the model regression equation (4).


Improved Rifamycin B Production by Nocardia mediterranei MTCC 14 under Solid-State Fermentation through Process Optimization.

Vastrad BM, Neelagund SE, Iiger SR, Godbole AM, Kulkarni V - Biochem Res Int (2014)

Surface and contour plot for rifamycin B production at varying concentrations of X4, galactose (GA), and X3, ribose (RI).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4209767&req=5

fig7: Surface and contour plot for rifamycin B production at varying concentrations of X4, galactose (GA), and X3, ribose (RI).
Mentions: Response surface methodology using central composite design was practical to optimize the levels of significant production parameters resulting from Plackett-Burman design experiments. Thirty experiments were carried out from the design and the experimental values are given in Table 5. All the experiments were carried out in duplicate; the mean value of rifamycin B yield was taken for statistical analysis. By applying multiple regression analysis on the experimental data, the following second-order polynomial equation was developed:(4)Rifamycin  B  (g/kgds) =+2306.89958−97.84583X4−244.48417X3  −14.31583X1−384.39167X10+6.26500X4X3  +1.50000X4X1−1.21000X4X10−2.11000X3X1  +20.15000X3X10−0.98000X1X10+4.42750X42  +9.07750X32+0.89750X12+22.55000X102.The effects of galactose (X4), ribose (X3), glucose (X1), and pH (X10) on rifamycin B production are reported in Table 7. Response surfaces for rifamycin B yield are shown in Figures 7–12, which give the surface and contour plots for the effect of galactose, ribose, glucose, and pH on the rifamycin B yield. Regression analysis of the experimental data (Table 7) showed that galactose and ribose had significant positive linear effects on rifamycin B yield, while glucose and pH had negative linear effect on rifamycin B yield. This was clear from the low P value obtained from the regression analysis. Among the four processes parameters, galactose was found to have the highest impact on rifamycin B yield as given by the highest linear coefficient (1.66) followed by ribose (0.23), while glucose (−0.40) and pH (−1.38) have negative linear effect. These production parameters also showed significant positive quadratic effects on rifamycin B yield indicating that rifamycin B production increased as the level of these factors increased and decreased as the level of these processes parameters decreased below certain values. Table also indicates that the interaction between ribose and pH and between galactose and ribose has significant effect on rifamycin B production and all other interactive variables are insignificant. Hence, only the term indicating interaction between ribose and pH and between galactose and ribose was included in the model regression equation (4).

Bottom Line: Optimum levels of the significant variables were decided by using a central composite design.At these optimum production parameters, the maximum yield of rifamycin B obtained experimentally (9.87 g/kgds dry sunflower oil cake) was found to be very close to its predicted value of 10.35 g/kgds dry sunflower oil cake.The mathematical model developed was found to fit greatly with the experimental data of rifamycin B production.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Biotechnology, S.E.T's College of Pharmacy, Dharwad, Karnataka 580002, India.

ABSTRACT
Optimization of various production parameters using response surface methodology (RSM) was performed to assess maximum yield of rifamycin B from Nocardia mediterranei MTCC 14. Plackett-Burman design test was applied to determine the significant effects of various production parameters such as glucose, maltose, ribose, galactose, beef extract, peanut meal, ammonium chloride, ammonium sulphate, barbital, pH, and moisture content on production of rifamycin B. Among the eleven variables tested, galactose, ribose, glucose, and pH were found to have significant effect on rifamycin B production. Optimum levels of the significant variables were decided by using a central composite design. The most appropriate condition for production of rifamycin B was found to be a single step production at galactose (8% w/w), ribose (3% w/w), glucose (9% w/w), and pH (7.0). At these optimum production parameters, the maximum yield of rifamycin B obtained experimentally (9.87 g/kgds dry sunflower oil cake) was found to be very close to its predicted value of 10.35 g/kgds dry sunflower oil cake. The mathematical model developed was found to fit greatly with the experimental data of rifamycin B production.

No MeSH data available.


Related in: MedlinePlus