Comprehensive Transcriptome Analyses of the Fructose-Fed Syrian Golden Hamster Liver Provides Novel Insights into Lipid Metabolism

Abstract

Dyslipidemia has been widely proven to contribute to cardiovascular diseases and other metabolic disorders, especially in insulin resistance and type 2 diabetes. The overproduction of VLDL is a significant characteristic of dyslipidemia, indicating the dysfunction of hepatic lipid metabolism, from triglyceride synthesis to transport. The fructose-fed Syrian golden hamster is an established animal model for the study of VLDL assembly with insulin resistance, however, it remains unknown how VLDL production is regulated at the transcriptional level due to the absence of a complete hamster genome. Here, we performed deep sequencing and constructed an mRNA-miRNA-lncRNA interaction network of Syrian golden hamster liver in order to reveal the global transcription profile and find potential RNA molecular regulation of VLDL production. We identified 4,450 novel multi-exon hamster lncRNAs and 755 miRNAs expressed in liver. Additionally, 146 differentially expressed coding genes, 27 differentially expressed lncRNA genes, as well as 16 differentially expressed miRNAs were identified. We then constructed an mRNA-miRNA-lncRNA interaction network that may potentially regulate VLDL production, and interestingly found several microRNA-centered regulatory networks. In order to verify our interpretation, miR-486 was selected for further experiments. Overexpression or down-regulation of miR-486 in fructose-fed hamsters resulted in altered hepatic expression of proteins involved in VLDL production, and in modulated levels of circulating VLDL. Our findings implicated that miR-486 is a potential regulator of circulating VLDL levels. These results provide new insights and a valuable resource for further study of the molecular mechanisms of VLDL secretion.

Fig 1. Overview of the data processing pipeline.

Fig 2. Basic features and conservation of hamster lncRNAs.

(a) The cumulative distributions of transcript lengths for the hamster lncRNAs (green), hamster protein-coding genes (blue), mouse lncRNAs (black), and mouse protein-coding genes (red). (b) The distribution of exon numbers for hamster lncRNAs (green), hamster protein-coding genes (blue), mouse lncRNAs (black), and mouse protein-coding genes (red). (c) The distribution of the number of isoforms identified for hamster lncRNA genes (green), hamster protein-coding genes (blue), mouse lncRNA genes (black), and mouse protein-coding genes (red). (d) The expression levels of hamster lncRNAs were lower than hamster protein-coding genes. Maximal expression abundance (log2-normalized FPKM counts as estimated by Cufflinks) of each lncRNA (blue) and protein-coding gene (green). (e) Sequence conservation of lncRNAs between hamster and other mammals. (f) Correlation analysis of hamster lncRNA and coding gene pairs. Black: random lncRNA-coding gene pairs. Green: neighbouring lncRNA-coding gene pairs. Red: different expression neighbouring lncRNA-coding gene pairs.

Fig 3. Differentially expressed liver protein-coding genes and lncRNAs.

(a) Differentially expressed liver protein-coding genes. (b) Differentially expressed liver lncRNA genes. (c) GO terms (biological processes) of the identified differentially expressed coding genes. (d) KEGG pathway analysis of the identified differentially expressed coding genes. (e) qPCR results for coding genes and lncRNAs. (Data were analyzed by the Δ Δ Ct method, the values represent the means with SD, n = 6).

Fig 4. Differentially expressed liver miRNAs and the interaction network.

(a) Differentially expressed liver miRNAs. (b) KEGG pathway analysis of the identified differentially expressed miRNAs. (c) qPCR results for miRNAs. (Data were analyzed by the Δ Δ Ct method, the values represent the means with SD, n = 10). (d) Validation of selected miRNAs. miRNAs from M to 6: marker (DL 2000), miR-10a-5p, miR-28-3p, miR-92-3p, miR-150-5p, miR-182-5p, miR-192-5p. (e) Differentially expressed mRNAs, miRNAs and lncRNAs interactions on VLDL secretion. This interaction network diagram was made by using Cytoscape.

Fig 5. miR-486 regulates the production of VLDL through the PI3K-Akt-Signaling Pathway by targeting PTEN and Foxo1a.

(a) Hepatic miR-486 levels determined by quantitative RT-PCR in hamsters injected with Adenovirus harboring miR-486 mimics and miR-486 antago, as well as a scrambled control. n = 6 per group. (b) Fast protein liquid chromatography (FPLC) analysis of sera from fructose-fed Syrian golden hamsters (n = 6) injected with lentivirus expressing miR-486. (c) Mean area under the curve (AUC) values calculated for VLDL fractions 14–16 isolated by FPLC from b. (d, h) Immunoblot analysis of hepatic Foxo1, Pten (d), and Mttp (h) in liver tissue from fructose-fed hamsters treated with miR-486 mimics and miR-486 antagonist showing expression levels of Foxo1. β-actin was used as a loading control. (e-g) Hepatic expression of Foxo1 (e), Pten (f), and Mttp (g) in hamsters injected with Adenovirus harboring miR-486 mimics and miR-486 antagonist, as well as a scrambled control. n = 6 per group.