STRUCTURAL CHARACTERIZATION OF GEMINI-BASED NANOPARTICLES FOR DELIVERY OF DNA
Cationic gemini surfactants have been used for delivery of DNA into cells. These cationic surfactants are known to strongly bind to DNA to form a complex. In the dilute regimen, when the gemini-DNA complexes are mixed with helper neutral lipids, they undergo spontaneous assembly to form particles that are able to transfect DNA into the cells. In this study, the structure of several gemini surfactants, gemini-DNA complexes and gemini-DNA-neutral lipids complexes were systematically examined by small angle x-ray scattering (SAXS). The gemini surfactants were found to form micelles of varying shapes and arrangements modulated by the nature of spacer region and tail lengths. This includes ellipsoidal and worm-like micelles (as in the case of the 12- s-12 series) and disk-shaped hexagonally packed micelles (as in the case of 16-3-16). In addition to the study of the gemini surfactants, the effect of varying the DNA: gemini charge ratio on the DNA-gemini assembly was studied. The scattering pattern has shown that in the presence of excess gemini surfactants, free unbound surfactants exist in the solution. Upon the addition of neutral lipids, DNA-gemini-neutral lipid complexes are formed. The scattering patterns of the latter showed evidence of a strong interaction of the neutral lipids with the free gemini surfactants and the overcharged DNA-gemini complexes. Effectively, overcharging DNA-gemini complexes seem to aid in its incorporation into the neutral lipid matrix. These findings shed the light on the structure of DNA-gemini-neutral lipid systems and provide insights into the factors that influence the spontaneity of the self-assembly process. More importantly, the presented work provides a general strategy that can be applied to the study of similar systems using small angle x-ray scattering. A helium and vacuum chambers were made to enable testing the feasibility of the technique at the Canadian Light Source. Further, a pipeline was written to automate the reduction and analysis of SAXS data.
DegreeMaster of Science (M.Sc.)
DepartmentPharmacy and Nutrition
SupervisorGrochulski, Pawel; Badea, Ildiko
CommitteeYang, Jian; Krol, Ed
Copyright DateMay 2014