(93s) A Bioinformatics Approach to Modeling Cytochrome P450 Gene Regulation in Hepatocytes

Transplant organ shortage as well as difficulty in predicting liver transplant failure has underscored the need for a better understanding of liver cell functions both in vitro and in vivo. Research into alternatives to whole organ transplantation, such as non-biological approaches, has met with limited success, presumably because the synthetic and metabolic functions of the liver are inadequately replaced. Better in vitro models of liver cells, termed primary hepatocytes, could facilitate the development of these approaches. Metabolic functions of the liver have been extensively studied using hepatocyte cells cultured in vitro. Genes involved in the specific metabolic pathways are often co-regulated by the same factors. Often regulation occurs via transcription through regulation of binding sites. Gene regulation plays important roles in the understanding of cellular pathways. An important family of genes involved in liver metabolism is the Cytochrome P450 genes (CYP). Cytochrome P450 genes play two important roles: (1) biosynthesis of steroids, fatty acids, and bile acids; (2) metabolism of endogenous and a wide variety of exogenous substrates, such as toxins and drugs. Microarray analysis of hepatocytes in vitro yields gene expression data over a period of time. Our focus is on the expression of Cytochrome P450 genes. Microarray data shows certain CYP genes are up regulated while others are down regulated (Baker et al., Chem. Res. Toxicol., 2001). Genes that show similar quantitative expression are not necessarily co-regulated. While co-expression is informative, we strive to understand the molecular basis for the co-regulation of genes involved in the same metabolic pathway. Bioinformatics has yielded powerful tools to aid in the process. After analyzing previously published data, a predictive model for a CYP pathway will be constructed from the genes that are known to be involved in the same pathway. Sequences for all the genes in a pathway will be assed computationally for putative transcription factor binding sites. Putative binding sites will then be assayed using RNAi methods. We expect that by removing specific genes from a pathway, we can force a noticeable change in hepatocyte metabolism, such as loss of function of Acetaminophen metabolism. We also will test our model by exposing cultured hepatocytes to different xenobiotics, thus inducing a Cytochrome P450 response that can be measured by measuring the level changes of RNA by RT-PCR. This integrated systems biology approach is expected to provide new insights into liver physiology and toxicology that can impact prescription and dosing of drugs as well as pharmaceutical lead screening using living hepatocytes.