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A nutrigenomic framework to identify time-resolving responses of hepatic genes in diet-induced obese mice

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Molecules and Cells

Abstract

Obesity and its related complications have emerged as global health problems; however, the pathophysiological mechanism of obesity is still not fully understood. In this study, C57BL/6J mice were fed a normal (ND) or high-fat diet (HFD) for 0, 2, 4, 6, 8, 12, 20, and 24 weeks and the time course was systemically analyzed specifically for the hepatic transcriptome profile. Genes that were differentially expressed in the HFD-fed mice were clustered into 49 clusters and further classified into 8 different expression patterns: long-term up-regulated (pattern 1), long-term downregulated (pattern 2), early up-regulated (pattern 3), early down-regulated (pattern 4), late up-regulated (pattern 5), late down-regulated (pattern 6), early up-regulated and late down-regulated (pattern 7), and early down-regulated and late up-regulated (pattern 8) HFD-responsive genes. Within each pattern, genes related with inflammation, insulin resistance, and lipid metabolism were extracted, and then, a protein-protein interaction network was generated. The pattern specific sub-network was as follows: pattern 1, cellular assembly and organization, and immunological disease, pattern 2, lipid metabolism, pattern 3, gene expression and inflammatory response, pattern 4, cell signaling, pattern 5, lipid metabolism, molecular transport, and small molecule biochemistry, pattern 6, protein synthesis and cell-to cell signaling and interaction and pattern 7, cell-to cell signaling, cellular growth and proliferation, and cell death. For pattern 8, no significant sub-networks were iden-tified. Taken together, this suggests that genes involved in regulating gene expression and inflammatory response are up-regulated whereas genes involved in lipid metabolism and protein synthesis are down-regulated during dietinduced obesity development.

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Authors and Affiliations

  1. Green Bio Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, 305-806, Korea

    Hyoung-Sam Heo, Hyojung Paik & Cheol-Goo Hur

  2. Division of Bio-Medical Informatics, Center for Genome Science, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Cheongwon, 363-951, Korea

    Hyoung-Sam Heo

  3. Department of Food Science and Nutrition, Catholic University of Daegu, Gyeongsan, 712-702, Korea

    Eunjung Kim

  4. Food and Nutritional Genomics Research Center, Kyungpook National University, Daegu, 702-701, Korea

    Eunjung Kim, Seon-Min Jeon, Eun-Young Kwon, Su-Kyung Shin & Myung-Sook Choi

  5. Department of Food Science and Nutrition, Kyungpook National University, Daegu, 702-701, Korea

    Seon-Min Jeon, Eun-Young Kwon, Su-Kyung Shin & Myung-Sook Choi

  6. Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, 443-749, Korea

    Hyojung Paik

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  1. Hyoung-Sam Heo
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Correspondence to Cheol-Goo Hur or Myung-Sook Choi.

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Heo, HS., Kim, E., Jeon, SM. et al. A nutrigenomic framework to identify time-resolving responses of hepatic genes in diet-induced obese mice. Mol Cells 36, 25–38 (2013). https://doi.org/10.1007/s10059-013-2336-3

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