Prediction of VEGF-C as a Key Target of Pure Total Flavonoids From Citrus Against NAFLD in Mice via Network Pharmacology

Figures

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  FIGURE 1. The whole workflow of network pharmacology strategy to screen common target nodes for NAFLD progression group and PTFC treatment group. ND, normal diet; HFD, high-fat diet; DEG, differentially expressed gene; STEM, short time-series expression miner; CTD, the comparative toxicogenomics database; WGCNA, weighted gene co-expression network analysis; SRING: string database.

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  FIGURE 2. Data normalization and hierarchical clustering. (A) Box plots of normalized data for expression profile of all samples. Data distribution before (left) and after (right) normalization. The vertical axis represents all samples. (B–F) Hierarchical clustering analysis of differentially expressed gene among the samples. Each gene is represented in each row and the column denotes each run. Scale bar denotes the Z-score fold change. The vertical axis represents all samples among pairwise comparisons of subgroups B vs. A, C vs. A, D vs. A, C vs. B and D vs. C. A, ND for 24-week; B, HFD for 16-week; C, HFD for 24-week; D, HFD for 24-week combined with PTFC intervention for 18-week.

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  FIGURE 3. Venn diagrams and STEM clustering analysis of the DEGs in NAFLD progression group and PTFC treatment group. (A) Venn diagrams showing the number of DEGs in the three pairwise comparisons in NAFLD progression group (left) and PTFC treatment group (right). (B) STEM clustering of DEGs expression patterns of NAFLD progression group (left) and PTFC treatment group (right). Each box shows a clustering of gene expression pattern. The cluster ID number is marked in the top left-hand corner of the box and the curve denotes gene expression tendency in different sample subgroups. The number in the middle is the number of DEGs. The P-value of clustered time series genes is marked in the bottom left-hand corner of each cluster box. The colored box denotes significant clustering (P < 0.05).

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  FIGURE 4. Gene-pathway networks construction. (A) Network of NAFLD progression group. (B) Network of PTFC treatment group.

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  FIGURE 5. Gene-pathway network construction based on CTD. (A) Network of NAFLD progression group. (B) Network of PTFC treatment group.

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  FIGURE 6. WGCNA and the protein-protein interaction network construction. (A) Gene dendrogram and modules colors maps showing modules of co-expressed DEGs of NAFLD progression group (left) and PTFC treatment group (right). Each module is labeled by a unique color (gray module is for DEGs unassigned). Each vertical line in the “leaf” represents a DEG. (B) Tables of module-trait relationship of NAFLD progression group (left) or PTFC treatment group (right). Each row corresponds to a module eigengene and each column represents a trait. Each cell reports the correlation coefficient and the P-value (in parenthesis) between each module and a trait. The left panel represents eight modules and the number of their member genes. The right panel is a color scale for module trait correlation from –1 to 1. (C). Protein-protein interaction network of NAFLD progression group (left) and of PTFC treatment group (right).

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  FIGURE 7. Screening the common hub DEGs between networks of NAFLD progression and PTFC treatment groups. (A) Gene-pathway network of NAFLD progression group. (B). Gene-pathway network of PTFC treatment group. (C) Merging networks of A and B.

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  FIGURE 8. The expression levels of VEGF-C and COL4A1. (A,B) Real-time PCR verification of the mRNA expression levels of VEGF-C and COL4A1. Relative transcript levels were calculated via the 2−ΔΔC(t) method and β-actin transcripts were used as the internal control. ∗P < 0.05, ∗∗P < 0.01, n = 6/group. (C,D) Western blot assay of the protein expression levels of VEGF-C and COL4A1. GAPDH was served as the loading control. ∗P < 0.05.

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  FIGURE 9. The transcript expression levels of CCL4 and CCR7. Real-time PCR verification of the mRNA expression levels of CCL4 and CCR7. Relative transcript levels were calculated via the 2−ΔΔC(t) method and β-actin transcripts were used as the internal control. ∗P < 0.05, ∗∗P < 0.01, n = 6/group.

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  FIGURE 10. Potential roles of VEGF-C in the progression of NAFLD and PTFC treatment. VEGF-C plays roles in lipid accumulation, obesity-related insulin resistant, inflammation as well as in fibrosis, which are also important characteristics in the progression of NAFLD. The effects of lipid reducing, anti-inflammation, anti-fibrosis and attenuation of insulin resistance of PTFC may be associated with targeting VEGF-C.