DOI QR코드

DOI QR Code

Optimization of medium for phenylalanine ammonia lyase production in E. coli using response surface methodology

  • Cui, Jian-Dong (Hebei Fermentation Engineering Research Center, College of Bioscience and Bioengineering, Hebei University of Science and Technology)
  • Received : 2009.01.16
  • Accepted : 2009.03.17
  • Published : 2010.01.01

Abstract

A culture medium for phenylalanine ammonia lyase (PAL) production in E. coli was developed following preliminary studies by means of response surface methodology (RSM). The medium components having significant effect on the production were first identified by using a fractional factorial design. Then, central composite design (CCD) was used to optimize the medium constituents and explain the combined effects of four medium constituents: glucose, yeast extract, $(NH_4)_2HPO_4$ and $MgSO_4$. A quadratic model was found to fit the PAL production. CCD revealed that the optimum values of the test variables for PAL production were glucose 28.2 g/L, yeast extract 5.01 g/L, $(NH_4)_2HPO_4$ 7.02 g/L and $MgSO_4$ 1.5 g/L. PAL production of 62.85 U/g, which was in agreement with the prediction, was observed in the verification experiment. In comparison to the production of basal medium, 1.8-fold increase was obtained.

Keywords

References

  1. H.Y. Yue, Q. P. Yuan and W. Ch. Wang, Biochem. Eng. J., 37, 231 (2007). https://doi.org/10.1016/j.bej.2007.05.002
  2. M. J. Fiske and J. F. Kane, J. Bacteriol., 160, 676 (1984).
  3. J. D. Cui and Y. Li, Korean J. Chem. Eng., In press (2009).
  4. J. Rosler, F. Krekel and N. Amrhein, Plant Physiol., 113, 175 (1997). https://doi.org/10.1104/pp.113.1.175
  5. H. Orum and O. F. Rasmussen, Appl. Microbiol. Biotechnol., 36, 745 (1992).
  6. J.D.B. Faulkner, J.G. Anson and M. F. Tuite, Gene., 143, 13 (1994). https://doi.org/10.1016/0378-1119(94)90598-3
  7. Sh. R. Jia, J. D. Cui and Y. Li, Biochem. Eng. J., 42, 193 (2008). https://doi.org/10.1016/j.bej.2008.06.010
  8. Y. R. Abdel-Fattah, H. M. Saeed and Y. M. Gohar, Process Biochem., 40, 1707 (2005). https://doi.org/10.1016/j.procbio.2004.06.048
  9. D.C Montgomery, Design and analysis of experiments, Singapore, Wiley Press, 125 (1984).
  10. C. Liyana-Pathirana and F. Shahidi, Food Chem., 9, 347 (2005).
  11. H. Lee, M. Song and S. H. Wang, Process Biochem., 38, 1685 (2003). https://doi.org/10.1016/S0032-9592(02)00259-5
  12. D.A. Bocchini, H. F. Alves-Prado and L. C. Baida, Process Biochem., 38, 727 (2002). https://doi.org/10.1016/S0032-9592(02)00207-8
  13. M. Avishek and G. Arun, Bioresource Tech., 99, 3685 (2008). https://doi.org/10.1016/j.biortech.2007.07.027
  14. M. P. Delisa, G. Rao and W.A. Weigand, Biotech. Bioeng., 6, 554 (1999).
  15. J. H. Lee, Y. J. Yoo and K. H. Par, Korean J. Chem. Eng., 8, 39 (1991). https://doi.org/10.1007/BF02697696
  16. J. Y. Jung, T. Khan and J. K. Park, Korean J. Chem. Eng., 24, 1 (2007). https://doi.org/10.1007/s11814-007-5001-8
  17. R. Sen, J. Chem. Technol. Biotechnol., 68, 263 (1997). https://doi.org/10.1002/(SICI)1097-4660(199703)68:3<263::AID-JCTB631>3.0.CO;2-8
  18. S. Akhnazarova and V. Kefarov, Experiment optimization in chemistry and chemical engineering, Moscow, Mir Publishers, 135 (1982).
  19. A. I. Khuri and J.A. Cornell, Response surfaces: design and analysis, New York, Marcel Dekker, 211 (1987).