Gerlinde Schwake, Simon Youssef, and Jan-Timm Kuhr contributed equally to this work.
Predictive modeling of non-viral gene transfer
Article first published online: 1 DEC 2009
Copyright © 2009 Wiley Periodicals, Inc.
Biotechnology and Bioengineering
Volume 105, Issue 4, pages 805–813, 1 March 2010
How to Cite
Schwake, G., Youssef, S., Kuhr, J.-T., Gude, S., David, M. P., Mendoza, E., Frey, E. and Rädler, J. O. (2010), Predictive modeling of non-viral gene transfer. Biotechnol. Bioeng., 105: 805–813. doi: 10.1002/bit.22604
- Issue published online: 20 JAN 2010
- Article first published online: 1 DEC 2009
- Accepted manuscript online: 1 DEC 2009 12:00AM EST
- Manuscript Accepted: 21 OCT 2009
- Manuscript Revised: 17 SEP 2009
- Manuscript Received: 16 JUN 2009
- Deutsche Forschungsgemeinschaft. Grant Numbers: SFB486-B10, SFB TR12
- mathematical modeling;
- gene transfer;
- single cell;
- transfection/gene expression
In non-viral gene delivery, the variance of transgenic expression stems from the low number of plasmids successfully transferred. Here, we experimentally determine Lipofectamine- and PEI-mediated exogenous gene expression distributions from single cell time-lapse analysis. Broad Poisson-like distributions of steady state expression are observed for both transfection agents, when used with synchronized cell lines. At the same time, co-transfection analysis with YFP- and CFP-coding plasmids shows that multiple plasmids are simultaneously expressed, suggesting that plasmids are delivered in correlated units (complexes). We present a mathematical model of transfection, where a stochastic, two-step process is assumed, with the first being the low-probability entry step of complexes into the nucleus, followed by the subsequent release and activation of a small number of plasmids from a delivered complex. This conceptually simple model consistently predicts the observed fraction of transfected cells, the cotransfection ratio and the expression level distribution. It yields the number of efficient plasmids per complex and elucidates the origin of the associated noise, consequently providing a platform for evaluating and improving non-viral vectors. Biotechnol. Bioeng. 2010. 105: 805–813. © 2009 Wiley Periodicals, Inc.