The discovery of RNA interference and the increasing understanding of disease genetics have created a new class of potential therapeutics based on oligonucleotides. This therapeutic class includes antisense molecules, small interfering RNA (siRNA), and microRNA modulators such as antagomirs (antisense directed against microRNA) and microRNA mimics, all of which function by altering gene expression at the translational level. While these molecules have the promise of treating a host of diseases from neurological disorders to cancer, a major hurdle is their inability to enter cells on their own, where they may render therapeutic effect. Nanotechnology is the engineering of materials at the nanometer scale and has gained significant interest for nucleic acid delivery due to its biologically relevant length-scale and amenability to multifunctionality. While a number of nanoparticle vehicles have shown promise for oligonucleotide delivery, there remains a lack of understanding of how nanoparticle coating and size affect these delivery processes. This dissertation seeks to elucidate some of these factors by evaluating oligonucleotide delivery efficiencies of a panel of iron oxide nanoparticles with varying cationic coatings and sizes. A panel of uniformly-sized nanoparticles was prepared with surface coatings comprised of various amine groups representing high and low pKas. A separate panel of nanoparticles with sizes of 40, 80, 150, and 200 nm but with the same cationic coating was also prepared.
Results indicated that both nanoparticle surface coating and nanoparticle hydrodynamic size affect transfection efficiency. Specific particle coatings and sizes were identified that gave superior performance. The intracellular fate of iron oxide nanoparticles was also tracked by electron microscopy and suggests that they function via the proton sponge effect. The research presented in this dissertation may aid in the rational design of improved nanoparticle delivery vectors for nucleic acid-based therapy.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/39520 |
| Date | 23 March 2011 |
| Creators | Shen, Christopher |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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