Metabolomics is a rapidly growing research field that studies the response of biological systems to environmental factors, disease states and genetic modifications. It aims at measuring the complete set of endogenous metabolites, i.e. the metabolome, in a biological sample such as plasma or cells. Because metabolites are the intermediates and end products of biochemical reactions, metabolite compositions and metabolite levels in biological samples can provide a wealth of information on on-going processes in a living system. Due to the complexity of the metabolome, metabolomic analysis poses a challenge to analytical chemistry. Adequate sample preparation is critical to accurate and reproducible analysis, and the analytical techniques must have high resolution and sensitivity to allow detection of as many metabolites as possible. Furthermore, as the information contained in the metabolome is immense, the data set collected from metabolomic studies is very large. In order to extract the relevant information from such large data sets, efficient data processing and multivariate data analysis methods are needed. In the research presented in this thesis, metabolomics was used to study mechanisms of polymeric gene delivery to retinal pigment epithelial (RPE) cells. The aim of the study was to detect differences in metabolomic fingerprints between transfected cells and non-transfected controls, and thereafter to identify metabolites responsible for the discrimination. The plasmid pCMV-β was introduced into RPE cells using the vector polyethyleneimine (PEI). The samples were analyzed using high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) coupled to a triple quadrupole (QqQ) mass spectrometer (MS). The software MZmine was used for raw data processing and principal component analysis (PCA) was used in statistical data analysis. The results revealed differences in metabolomic fingerprints between transfected cells and non-transfected controls. However, reliable fingerprinting data could not be obtained because of low analysis repeatability. Therefore, no attempts were made to identify metabolites responsible for discrimination between sample groups. Repeatability and accuracy of analyses can be influenced by protocol optimization. However, in this study, optimization of analytical methods was hindered by the very small number of samples available for analysis. In conclusion, this study demonstrates that obtaining reliable fingerprinting data is technically demanding, and the protocols need to be thoroughly optimized in order to approach the goals of gaining information on mechanisms of gene delivery.

Gene therapy is the therapeutic delivery of nucleic acid sequences into cells, where they can replace a gene that is missing, mutated or poorly expressed. It is a potential treatment to cure e.g. genetic diseases, viral infections and various cancers. The nucleic acid needs to be delivered across the cell membrane and into the nucleus to affect the gene expression. Anionic nucleic acids need a cationic carrier, such as a cationic liposome, to enable their delivery into the cells. The liposomes used in gene delivery usually contain both a cationic lipid to associate with the nucleic acid and a neutral helper lipid to stabilize the structure. The liposome-nucleic acid complex is called a lipoplex. The cationic carrier must include or function as a cell-penetrating enhancer (CPE) to be able to translocate across the cell membrane into the cytosol and to the nucleus. The experimental part of this work was aimed at developing and characterizing an innovative poly-cationic liposomal platform for gene delivery, using a novel synthetic CPE. The CPE used in this study is an oligo-guanidyl derivative (OGD) that had either 4 (OGD4) or 6 (OGD6) cationic charges. Liposomes were surface-engineered with OGD, obtaining a cationic formulation that was then exploited for DNA loading. The study has two main characterization steps: Step 1 was to decorate liposomes with OGD by post insertion using increasing amounts of OGD, and determine the vesicle size and zeta potential by dynamic light scattering (DLS). Step 2 involved DNA loading by post insertion into the cationic liposomes with increasing amounts of DNA. The lipoplex size and zeta potential was determined by DLS, the complexation by electrophoresis, and the thermodynamics of the cationic liposome/DNA association by isothermal titration calorimetry (ITC). The measurements were performed in isotonic buffers (HEPES pH 7.4 and citrate pH 5) and in lower ionic strength TRIS buffer (pH 7.4). The aim of the characterization studies was first to find a liposome composition that includes just enough OGD to obtain a sufficiently high zeta potential and a uniform, sufficiently small size. The optimal formulation contained either 10 % of OGD4 or 5 % of OGD6 of the total lipid amount. The second step was to find the highest stable DNA loading for the lipoplexes. All the characterization studies were performed on OGD4 lipoplexes in TRIS buffer. The optimal OGD4/DNA N/P (nitrogenous/phosphorous) ratio was found to be around 5. Further investigation is needed to determine the best lipoplex composition and manufacturing method using an isotonic buffer. A DNA release study remains to be performed prior to further in vitro and in vivo studies.