Bioethics
Electronic Journal of Biotechnology ISSN: 0717-3458 Vol. 13 No. 5, Issue of September 15, 2010
© 2010 by Pontificia Universidad Católica de Valparaíso -- Chile Received March 6, 2010 / Accepted May 26, 2010
DOI: 10.2225/vol13-issue5-fulltext-6  
RESEARCH ARTICLE

Optimization of polyethylenimine-mediated transient transfection using response surface methodology design

Qiangyi Fang*
Shanghai Institutes for Biological Sciences
Chinese Academy of Sciences
Shanghai, China
E-mail: hicell@gmail.com

Bingqian Shen
College of Pharmaceutical Sciences
Nankai University
Tianjin, China

*Corresponding author

Keywords: bioreactor, human tissue kallikrein, transient gene expression.

Abbreviations:

ANOVA: Analysis of variance
CHO: chinese hamster ovary
GFP: green fluorescent protein
HEK 293-F: human embryonic kidney cell
hTK: human tissue kallikrein
IOD: integral optic density
PCR: polymerase chain reaction
PEI: polyethylenimine
RSM: response surface methodology
TGE: transient gene expression
TproK: tissue prokallikrein

Abstract   Full Text

Response surface methodology was undertaken to optimize the polyethylenimine-mediated transient transfection of suspension cultured HEK 293-F cells. A total of 15 combinations were designed according to Box-Behnken design to identify the effects of DNA concentration, polyethylenimine concentration and incubation time on transient transfection efficiency. The highest integral optic density of green fluorescent protein presenting r-protein yield was accessed using a DNA concentration of 1.75 µg/mL, a polyethylenimine concentration of 10.5 µg/mL, and an incubation time of 11.8 min. Analysis of variance demonstrated that the experimental values fit well with a quadratic model. The RSM-optimized transient transfection resulted in greater production of human tissue prokallikrein (TproK) than non-RSM-optimized conditions: protein yield was 32.0 mg/L and the maximum viable cell density reached 3.57 x 106 cells/mL in a 5 L stirred-tank bioreactor culture.

Supported by UNESCO / MIRCEN network