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Received November 10, 2007
Accepted February 27, 2008
- This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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A simple unstructured model-based control for efficient expression of recombinant porcine insulin precursor by Pichia pastoris
1State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, P.R., China 2Department of Biotechnology, Jiangxi Agricultural University, 10 Yingshang Road, Nanchang 330045, P.R., China
guo_mj@ecust.edu.cn
Korean Journal of Chemical Engineering, September 2008, 25(5), 1065-1069(5), 10.1007/s11814-008-0174-3
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Abstract
Based on the fact that Pichia cell growth follows a Monod equation under the condition of methanol concentration limitation, a kinetics model of recombinant methylotrophic yeast Pichia pastoris expressing porcine insulin precursor (PIP) was developed in the quasi-steady state in the induction phase. The model revealed that the relationship between specific growth rate (μ) and substrate methanol concentration was in accord with the Monod equation. The fermentation kinetic parameters maximum specific growth rate (μmax), saturation constant (Ks) and maintenance coefficient (M) were estimated to be 0.101 h.1, 0.252 g l.1, and 0.011 g MeOH g.1 DCW h.1, respectively. The unstructured model was validated in methanol induction phase with different initial cell densities. Results showed that the maximum specific protein production rate (qp.max) of 0.098 mg g.1 DCW h.1 was achieved when μ was kept at 0.016 h.1, and the maximum yield of PIP reached 0.97 g l.1, which was 1.5-fold as that of the control. Therefore, the simple Monod model proposed has proven to be a robust control system for recombinant porcine insulin precursor production by P. pastoris on pilot scale, which would be further applied on production scale.
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Zhang WH, Bevins MA, Plantz BA, Smith LA, Meagher MM, Biotechnol. Bioeng., 70(1), 1 (2000)
Li ZJ, Zhao QH, Liang H, Jiang SL, Chen T, Grella D, Shearon C, Bottaro DP, Sim BKL, Biotechnol. Lett., 24(19), 1631 (2002)
Zhou XS, Zhang YX, Biotechnol. Lett., 24(17), 1449 (2002)
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Curvers S, Brixius P, Klauser T, Thommes J, Weuster-Botz D, Takors R, Wandrey C, Biotechnol. Prog., 17(3), 495 (2001)
Ren HT, Yuan JQ, Bellgardt KH, J. Biotechnol., 106, 53 (2003)
Curvers S, Linneman J, Klauser T, Wandrey C, Takors R, Chemie Ingenieur Technik, 73, 1615 (2001)
Guo M, Chu J, Zhang S, Acta Microbiol. Sinica., 41, 617 (2001)
Cos O, Serrano A, Montesinos JL, Ferrer P, Cregg JM, Valero F, J. Biotechnol., 116, 321 (2005)
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Pais JM, Varas L, Valdes J, Cabello C, Rodriguez L, Mansur M, Biotechnol. Lett., 25(3), 251 (2003)
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