QSB: Quantitative Systems Approach to Hepatic Metabolism: To Elucidate the Effect of Tumor Necrosis Factor-alpha

Michigan State University, East Lansing MI

Investigators

Abstract

The overall goal of this project is to develop a quantitative systems approach to elucidate the role of elevated free fatty acids and tumor necrosis factor-alpha on hepatic metabolism. Mounting evidence suggests that elevated levels of free fatty acids along with tumor necrosis factor-alpha in the plasma play an important role in regulating hepatic metabolism. Fatty acids are involved in the generation of secondary messengers for signal transduction, regulation of hepatic enzyme activity, mediators of gene expression, and storage of metabolic energy. Similarly, evidence suggests tumor necrosis factor-alpha plays a role in mediating lipid metabolism and triggers a complicated array of intracellular signals. Current mechanistic understanding of lipid metabolism is limited due to the lack of comprehensive information on the interplay of genes and proteins that may act in concert, or in opposition, in their regulation of metabolic enzymes. This short-coming is primarily due to traditional approaches, that measure a few physiological, biochemical or genetic markers, which provide limited insight into the overall molecular mechanisms involved. A "systems biology" approach reconstructs the associations that lead to a system's behavior by integrating the information derived from RNA, protein, and metabolite expression profiles as a function of its surrounding environment. The ability to quantitate expression levels of multiple genes and proteins, corresponding to a cellular metabolic state and/or environment, provides a more comprehensive and integrative approach to understanding hepatic lipid metabolism and elucidating relevant intracellular information. In summary, this project seeks to develop a quantitative framework to obtain fundamental knowledge of hepatocyte metabolism that will be subsequently applied to study the more specific aspects of Type 2 diabetes and other metabolic diseases. The quantitative framework developed in this proposal is applicable to other cellular systems.