00043
LIPOPOLYMER-MEDIATED TRANSGENE DELIVERY TO HUMAN STEM CELLS

Saturday, February 18, 2017
Exhibit Hall (Hynes Convention Center)
Frea Mehta, Arizona State University, Tempe, AZ
Genetic manipulation of mammalian cell lines has widespread applications in biomedical research ranging from disease modeling to therapeutic development. Mammalian cells are generally difficult to genetically engineer, but exogenous nucleic acids can be expressed by viral, chemical, or non-chemical means. Chemical transfections are simpler in practice than both viral and non-chemical delivery of genetic material, but often suffer from cytotoxicity and low efficiency. Novel aminoglycoside antibiotic-derived lipopolymers have been synthesized to mediate transgene delivery to mammalian cells. These polymers are comprised of either paromomycin or apramycin cross-linked with glycerol diglycidylether and derivatized with stearoyl chloride in varying molar ratios. In this work, three previously identified target lipopolymers were screened against a library of human embryonic and induced pluripotent stem cell lines. Cells were transfected with a plasmid encoding green fluorescent protein (GFP) and expression was quantified with flow cytometry 48 hours after transfection. Transfection efficiency was evaluated between three distinct lipopolymers and four lipopolymer:DNA mass ratios. GFP expression was compared to that of cells transfected with commercially available chemical gene delivery reagent controls–JetPEI, Lipofectamine, and Fugene–at their recommended reagent:DNA ratios. In H9 embryonic stem cells, apramycin-based lipopolymers attained 25.47±6.88% transfection efficiency, compared to 10.22±1.29% in cells transfected with Lipofectamine. These lipopolymers display higher transfection efficiency than commercially available chemical gene delivery reagents with less cytotoxicity. Improved transgene expression in stem cell lines allows for improved research methods. Human stem cell-derived neurons that have been genetically manipulated to express phenotypic characteristics of aging can be utilized to model neurodegenerative diseases, elucidating information about these diseases that would be inaccessible in unmanipulated tissue.