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Predicting Gene Silencing Through the Spatiotemporal Control of siRNA Release from Photo-responsive Polymeric Nanocarriers
Published on: July 21, 2017
Predicting Gene Silencing Through the Spatiotemporal Control of siRNA Release from Photo-responsive Polymeric
Chad T Greco1, Thomas H Epps2, Millicent O Sullivan3
1Department of Chemical and Biomolecular Engineering, University of Delaware.
Abstract:
New materials and methods are needed to better control the binding vs. release of nucleic acids for a wide range of applications that require the precise regulation of gene activity. In particular, novel stimuli-responsive materials with improved spatiotemporal control over gene expression would unlock translatable platforms in drug discovery and regenerative medicine technologies. Furthermore, an enhanced ability to control nucleic acid release from materials would enable the development of streamlined methods to predict nanocarrier efficacy a priori, leading to expedited screening of delivery vehicles. Herein, we present a protocol for predicting gene silencing efficiencies and achieving spatiotemporal control over gene expression through a modular photo-responsive nanocarrier system. Small interfering RNA (siRNA) is complexed with mPEG-b-poly(5-(3-(amino)propoxy)-2-nitrobenzyl methacrylate) (mPEG-b-P(APNBMA)) polymers to form stable nanocarriers that can be controlled with light to facilitate tunable, on/off siRNA release. We outline two complementary assays employing fluorescence correlation spectroscopy and gel electrophoresis for the accurate quantification of siRNA release from solutions mimicking intracellular environments. Information gained from these assays was incorporated into a simple RNA interference (RNAi) kinetic model to predict the dynamic silencing responses to various photo-stimulus conditions. In turn, these optimized irradiation conditions allowed refinement of a new protocol for spatiotemporally controlling gene silencing. This method can generate cellular patterns in gene expression with cell-to-cell resolution and no detectable off-target effects. Taken together, our approach offers an easy-to-use method for predicting dynamic changes in gene expression and precisely controlling siRNA activity in space and time. This set of assays can be readily adapted to test a wide variety of other stimuli-responsive systems in order to address key challenges pertinent to a multitude of applications in biomedical research and medicine.
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