AbstractsBiology & Animal Science

The rate of nonalcoholic fatty liver disease (NAFLD) such as steatosis and nonalcoholic steatohepatitis (NASH) in populations is continuing to grow vigorously and became a worldwide public health issue. To understand the liver disease progression one needs to investigate complex interactions occurring within biological systems. Systems biology tries to understand the interactions within biological systems by means of mathematical models. Exploiting this approach I want to describe interactions of genes, proteins and metabolites that are involved in nonalcoholic fatty liver disease. Molecular data from liver tissue samples of three mouse strains (A/J, C57Bl6 and PWD) under two different conditions: 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC)-treated and untreated (control) were analyzed. Each of these mouse strains shows different degrees of the disease under DDC treatment displaying high, low, and no steatohepatitis-like phenotypes for A/J, C57Bl6 and PWD, respectively. In this work I performed pathway analysis using gene expression data of mouse liver samples and identified metabolism of histidine, beta-alanine, purine along with glycolysis and gluconeogenesis pathways as top hit candidates that may be involved in liver dysfunction. Furthermore, gene expression and metabolite data of the arachidonic acid metabolism were found to be deregulated and this pathway was used for kinetic modeling. Genes and metabolites of S-adenosylmethionine (SAMe) metabolism were found to be perturbed under DDC-treatment. In addition, I have developed a novel enrichment analysis approach that may be used for identification of the most relevant fully coupled modules in a disease context. The approach includes three steps: 1) obtain fully coupled reactions which represent a module, 2) use gene expression data of a disease context to obtained marked correlated modules and 3) select modules in which at least one gene is differentially expressed between normal and disease conditions. Aforementioned steps are used to identify liver disease specific modules such as modules of pentose phosphate pathway and hepatic SAMe metabolism which are linked to oxidative stress. Furthermore, I also identified a module of cholesterol metabolism which is linked to apoptosis along with a module of pyrimidine catabolism, for which experimentally measured genes and metabolites were also found to be deregulated. The goal was to identify modules for which genes and metabolites are perturbed under DDC-treatment. The identified modules may be involved in liver disease and they can be used to build kinetic models for better understanding of the liver disease progression. Thus, in addition to enrichment analysis of fully coupled modules, I developed an approach which is based on elementary flux modes (EFMs). In this approach initially differentially regulated metabolites due to DDC-treatment were identified. Then reactions which can produce differentially regulated metabolites were used as a target set. For each reaction in the target set, 50 EFMs that…