Integrating physiological, metabolic and genetic information to identify the mechanisms of free fatty acid toxicity to hepatoma cells

The development of novel high-throughput techniques has made it possible to identify the global metabolic and genetic responses of the cells under a variety of conditions. The challenge is to efficiently analyze and relate the multi-source high-throughput data to generate novel information about cellular responses. The contributions of this thesis is the characterization of physiological, global metabolic and genetic alterations caused by different types of free fatty acids (FFAs) and tumor necrosis factor alpha (TNF-alpha) in the context of lipotoxicity, and the development of systems-biology frameworks to integrate multi-source information.; In the first part of the research, the toxicity of different types of free fatty acids was investigated. Among the different types of FFAs, only saturated FFA (palmitate) was toxic to the cells. Interactive effects of palmitate and TNF-alpha were observed on the toxicity. The reactive oxygen species (ROS) mediating the palmitate-cytotoxicity were identified to be hydrogen peroxide and hydroxyl radicals. In the next part, the differences in the metabolism of the cells in response to different types of FFA were investigated by applying metabolic flux analysis (MFA). It was identified that palmitate reduced the synthesis of glutathione by reducing cysteine uptake, caused by a reduction in the levels of cystine transporter xCT. Supplementing cysteine to the cells reduced the toxicity significantly. The global genetic changes caused by exposure to FFAs and TNF-alpha were identified by microarray analyses. Two novel methods were developed to integrate genomic and metabolic/physiological information. In the first method, the genes that regulate multiple cellular responses were identified by the dual response genetic algorithm partial least squares (GA/PLS) analysis. This method identified that NADH dehydrogenase and mitogen activated protein kinases (MAPKs) regulate cytotoxicity and TG accumulation. These predictions were experimentally verified. Finally, a novel Bayesian regression mixture model-based framework was developed to incorporate the gene ontology (GO) information to select the genes that could discriminate between the subpopulations. It was identified that incorporation of prior information improved the classification of the genes. Important roles of lysosomal ATPases and adenylate cyclase in mediating the toxicity were identified by this analysis, which were experimentally validated. Thus, in this research, the multiple alterations responsible for mediating palmitate-toxicity to hepatoma cells were identified and novel frameworks were developed to integrate multi-source high-throughput information.