Author(s): Kim S, Sohn I, Ahn JI, Lee KH, Lee YS,
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Abstract To understand the molecular mechanisms underlying alterations in the pathophysiologic status of dietary obesity, we examined hepatic genes differentially expressed in a long-term high-fat intake-induced obesity mouse model. C57BL/6J male mice were fed with two kinds of diets for 12 weeks; a low-fat diet (LFD), a high-fat diet (HFD; n=8), and the expression levels of approximately 10,000 transcripts in liver tissues from the two groups were assessed using cDNA microarray analysis. Twelve-week feeding with the HFD resulted in significant increase in body weight, visceral fat accumulation and circulating cholesterol concentration, compared with the LFD group. The cDNA microarray analysis revealed marked differences in the expressions of 97 hepatic genes. These genes were categorized into seven groups:metabolism; defense, stress, and inflammation responses; signal transduction, apoptosis, and cell cycle; transcription regulation; protein synthesis and modification; transport; and cellular adhesion, cytoskeleton and trafficking. The expression of genes involved in fatty acid catabolism and ketone body synthesis, such as acyl-CoA oxidase1 (Acox1) and HMG-CoA lyase (Hmgcl), was significantly increased, and expression of genes involved in lipogenesis and cholesterol synthesis, such as acetyl-CoA synthetase2 (Acs2), fatty acid synthase (Fasn), and squalene epoxidase (Sqle), was drastically decreased in the HFD group. Interestingly, the genes implicated in defense and stress responses, such as glutathione S-transferases (GSTs) and heat shock proteins (Hsps), were also highly represented in the HFD group. Besides, a number of previously unappreciated regulatory molecules were changed by the HFD. These results revealed a transcriptional adaptation to long-term HFD and provided interesting information about the molecules involved in the development and maintenance of the obesity phenotype in vivo.
This article was published in Gene
and referenced in Journal of Proteomics & Bioinformatics