Medium Optimization for Recombinant Soluble Arginine Deiminase Expression in Escherichia coli Using Response Surface Methodology

Title:Medium Optimization for Recombinant Soluble Arginine Deiminase Expression in Escherichia coli Using Response Surface Methodology

Volume: 18 Issue: 11

Author(s): Mahboubeh Zarei, Navid Nezafat, Mohammad Hossein Morowvat, Ali Dehshahri, Mohammad Bagher Ghoshoon, Aydin Berenjian and Younes Ghasemi*

Affiliation:

• Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz,Iran

Keywords: Arginine deiminase, response surface methodology, media optimization, recombinant production, E. coli, Mycoplasma hominis.

Abstract: Objective: Optimization of the medium for recombinant arginine deiminase production in E. coli was performed using response surface methodology. This is the first study of optimization of recombinant arginine deiminase production in E. coli by the use of response surface methodology.

Methods: A Mycoplasm arginine deiminase gene was computationally optimized and inserted into pET-3a (+) expression vector. The synthetic pET3a-arginine deiminase construct was cloned and overexpressed in E. coli. The effect of glucose, NH4Cl and MgSO4.7H2O concentrations on the expression of intracellular soluble arginine deiminase was investigated using central composite design (CCD).

Results: The maximum arginine deiminase activity (U/mL) was obtained in optimal concentrations g/L of glucose, 6.6; NH4Cl, 1.81; MgSO4.7H2O, 0.94; KH2PO4, 3.0; Na2HPO4, 6.78; NaCl, 0.5; CaCl2, 0.1 mL/L (1M), which was about 6.6 fold higher than that in M9 standard medium.

Conclusion: The obtained result can be utilized for large-scale production of this enzyme and related recombinant protein.

Cite this article as:

Zarei Mahboubeh, Nezafat Navid , Morowvat Hossein Mohammad, Dehshahri Ali , Ghoshoon Bagher Mohammad , Berenjian Aydin and Ghasemi Younes *, Medium Optimization for Recombinant Soluble Arginine Deiminase Expression in Escherichia coli Using Response Surface Methodology, Current Pharmaceutical Biotechnology 2017; 18 (11) . https://dx.doi.org/10.2174/1389201019666180115144752