Differential Expression of MicroRNAs in Adipose Tissue after Long-Term High-Fat Diet-Induced Obesity in Mice

Obesity is a major health concern worldwide which is associated with increased risk of chronic diseases such as metabolic syndrome, cardiovascular disease and cancer. The elucidation of the molecular mechanisms involved in adipogenesis and obesogenesis is of essential importance as it could lead to the identification of novel biomarkers and therapeutic targets for the development of anti-obesity drugs. MicroRNAs (miRNAs) have been shown to play regulatory roles in several biological processes. They have become a growing research field and consist of promising pharmaceutical targets in various fields such as cancer, metabolism, etc. The present study investigated the possible implication of miRNAs in adipose tissue during the development of obesity using as a model the C57BLJ6 mice fed a high-fat diet

Brown Adipose Tissue Responds to Cold and Adrenergic Stimulation by Induction of FGF21

Fibroblast growth factor-21 (FGF21) is a pleiotropic protein involved in glucose, lipid metabolism and energy homeostasis, with main tissues of expression being the liver and adipose tissue. Brown adipose tissue (BAT) is responsible for cold-induced thermogenesis in rodents. The role of FGF21 in BAT biology has not been investigated. In the present study, wild-type C57BL/6J mice as well as a brown adipocyte cell line were used to explore the potential role of cold exposure and beta 3-adrenergic stimulation in the expression of FGF21 in BAT. Our results demonstrate that short-term exposure to cold, as well as beta 3-adrenergic stimulation, causes a significant induction of FGF21 mRNA levels in BAT, without a concomitant increase in FGF21 plasma levels. This finding opens new routes for the potential use of pharmaceuticals that could induce FGF21 and, hence, activate BAT thermogenesis. (C) 2011 The Feinstein Institute for Medical Research, www.feinsteininstitute.or

Hepatic Gene Expression Profiling in Nrf2 Knockout Mice after Long-Term High-Fat Diet-Induced Obesity

Introduction. The transcription factor NFE2-related factor 2 (Nrf2) is a central regulator of antioxidant and detoxification gene expression in response to electrophilic or oxidative stress. Nrf2 has recently been shown to cross-talk with metabolic pathways, and its gene deletion protected mice from high-fat-diet-(HFD-) induced obesity and insulin resistance. This study aimed to identify potential Nrf2-regulated genes of metabolic interest by comparing gene expression profiles of livers of wild-type (WT) versus Nrf2 knockout (Nrf2-KO) mice after a long-term HFD. Methods. WT and Nrf2-KO mice were fed an HFD for 180 days; total RNA was prepared from liver and used for microarray analysis and quantitative real-time RT-PCR (qRT-PCR). Results. The microarray analysis identified 601 genes that were differentially expressed between WT and Nrf2-KO mice after long-term HFD. Selected genes, including ones known to be involved in metabolic regulation, were prioritized for verification by qRT-PCR: Cyp7a1 and Fabp5 were significantly overexpressed in in contrast, Car, Cyp2b10, Lipocalin 13, Aquaporin 8, Cbr3, Me1, and Nqo1 were significantly underexpressed in Nrf2-KO mice. Conclusion. Transcriptome profiling after HFD-induced obesity confirms that Nrf2 is implicated in liver metabolic gene networks. The specific genes identified here may provide insights into Nrf2-dependent mechanisms of metabolic regulation

Hepatic Gene Expression Profiling in Nrf2 Knockout Mice after Long-Term High-Fat Diet-Induced Obesity

Introduction. The transcription factor NFE2-related factor 2 (Nrf2) is a central regulator of antioxidant and detoxification gene expression in response to electrophilic or oxidative stress. Nrf2 has recently been shown to cross-talk with metabolic pathways, and its gene deletion protected mice from high-fat-diet-(HFD-) induced obesity and insulin resistance. This study aimed to identify potential Nrf2-regulated genes of metabolic interest by comparing gene expression profiles of livers of wild-type (WT) versus Nrf2 knockout (Nrf2-KO) mice after a long-term HFD. Methods. WT and Nrf2-KO mice were fed an HFD for 180 days; total RNA was prepared from liver and used for microarray analysis and quantitative real-time RT-PCR (qRT-PCR). Results. The microarray analysis identified 601 genes that were differentially expressed between WT and Nrf2-KO mice after long-term HFD. Selected genes, including ones known to be involved in metabolic regulation, were prioritized for verification by qRT-PCR: Cyp7a1 and Fabp5 were significantly overexpressed in Nrf2-KO mice; in contrast, Car, Cyp2b10, Lipocalin 13, Aquaporin 8, Cbr3, Me1, and Nqo1 were significantly underexpressed in Nrf2-KO mice. Conclusion. Transcriptome profiling after HFD-induced obesity confirms that Nrf2 is implicated in liver metabolic gene networks. The specific genes identified here may provide insights into Nrf2-dependent mechanisms of metabolic regulation

Hierarchical clustering (HCL) and Principal Component Analysis (PCA).

<p>HCL (A) and PCA analysis (B) for 18 mmu-miRs validated by qPCR. The clustering results were similar to those acquired by the miRNA profiling.</p

K-means clustering details.

<p>K-means clustering details.</p

Figure of merit (FOM) vs. no. of clusters graph for the k-means cluster algorithm.

<p>A figure of merit is an estimate of the predictive power of a clustering algorithm. The lower the adjusted FOM value is, the higher the predictive power of the algorithm. The value of the adjusted FOM for the k-means run decreases steeply until the number of clusters reaches 7, after which it levels out. This suggests that, for this data set, k-means performs optimally for 7 clusters and that any additional clusters produced will not add to the predictive value of the algorithm.</p

K-means clustering identified 10 clusters.

<p>This non-hierarchial method initially takes the number of components of the population equal to the final required number of clusters. In this step itself the final required number of clusters is chosen such that the points are mutually farthest apart. Next, it examines each component in the population and assigns it to one of the clusters depending on the minimum distance. The centroid's position is recalculated everytime a component is added to the cluster and this continues until all the components are grouped into the final required number of clusters. A. K-means clustering of profiles and B. Centroids.</p

GO terms annotation of the validated target genes of the down-regulated mmu-miRNAs after HFD feeding.

<p>The most significant functions of the enriched miRNAs are highlighted in red color.</p

miRNA relative expression in mice fed a standard or a high-fat diet for 5 months.

<p>The miRNA levels were measured by quantitative RT-PCR in white adipose tissue from mice fed a standard or a high-fat diet for 5 months (n = 8 for each diet type). The RT-PCR was performed in triplicate wells for each individual sample. Bars show means±standard deviation. * p<0.0001, † p<0.001. SD; standard diet, HFD; high-fat diet.</p