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Received May 5, 2016
Accepted December 23, 2016
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Medium optimization for high yield production of extracellular human interferon-γ from Pichia pastoris: A statistical optimization and neural network-based approach
Biochemical Engineering Laboratory, Department of Bioscience and Bioengineering, Indian Institute of Technology, Guwahati 781039, Assam, India
veeranki@iitg.ernet.in
Korean Journal of Chemical Engineering, April 2017, 34(4), 1109-1121(13)
https://doi.org/10.1007/s11814-016-0358-1
https://doi.org/10.1007/s11814-016-0358-1
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Abstract
Medium development for high level expression of human interferon gamma (hIFN-γ) from Pichia pastoris (GS115) was performed with the aid of statistical and nonlinear modeling techniques. In the initial screening, gluconate and glycine were found to be key carbon and nitrogen sources, showing significant effect on production of hIFN-γ. Plackett-Burman screening revealed that medium components., gluconate, glycine, KH2PO4 and histidine, have a considerable impact on hIFN-γ production. Optimization was further proceeded with Box-Behnken design followed by artificial neural network linked genetic algorithm (ANN-GA). The maximum production of hIFN-γ was found to be 28.48mg/L using Box-Behnken optimization (R2=0.98), whereas the ANN-GA based optimization had displayed a better production rate of 30.99mg/L (R2=0.98), with optimal concentration of gluconate=50 g/L, glycine=10.185 g/L, KH2PO4=35.912 g/L and histidine 0.264 g/L. The validation was carried out in batch bioreactor and unstructured kinetic models were adapted. The Luedeking-Piret (L-P) model showed production of hIFN-γ was mixed growth associated with the maximum production rate of 40mg/L of hIFN-γ production.
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References
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Prabhu AA, Veeranki VD, Dsilva SJ, Process Biochem., 51(6), 709 (2016)
Plackett RL, Burman JP, Biometrika., 33, 305 (1946)
Box GEP, Behnken DW, Technometrics, 2, 455 (1960)
Maran JP, Manikandan S, Priya B, Gurumoorthi P, J. Food Sci. Technol., 52, 92 (2013)
Song X, Mitnitski A, MacKnight C, Rockwood K, J. Am. Geriatr. Soc., 52, 1180 (2004)
Desai KM, Survase SA, Saudagar PS, Lele SS, Singhal RS, Biochem. Eng. J., 41, 266 (2008)
Khayet M, Cojocaru C, Sep. Purif. Technol., 86, 171 (2012)
Christova P, Todorova K, Timtcheva I, Nacheva G, Karshikoff A, Nikolov P, Zeitschrift Fur Naturforschung., 58, 288 (2003)
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Yang J, Moyana T, MacKenzie S, Xia Q, Xiang J, Appl. Environ. Microbiol., 64, 2869 (1998)
Klockner W, Buchs J, Trends Biotechnol., 30, 307 (2012)
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Sreekrishna K, Brankamp RG, Kropp KE, Blankenship DT, Tsay JT, Smith PL, Wierschke JD, Subramaniam A, Birkenberger LA, Gene, 190, 55 (1997)
Hu SY, Li LW, Qiao JJ, Guo YJ, Cheng LS, Liu J, Protein Expr. Purif., 47(1), 249 (2006)
Prabhu AA, Chityala S, Garg Y, Dasu VV, Prep. Biochem. Biotechnol., 1, 1 (2016)
Prabhu AA, Jayadeep A, Prep. Biochem. Biotechnol., 1 (2016)
