Capg enhances proliferation, adipogenesis, and inflammatory response in preadipocytes: insights from bioinformatics analysis and functional validation

Figures

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  Figure 1. Identification and overlap of differentially expressed genes (DEGs) in atherosclerotic datasets. (A, B) Volcano plots visualizing DEGs in the (A) GSE76812 and (B) GSE57659 datasets. Genes with statistically significant up-regulation (red) and down-regulation (blue) were identified using thresholds of |log2 fold change| > 1 and adjusted p-value (FDR) < 0.05. Grey dots represent non-significant genes. The top 20 significantly dysregulated genes are labeled. (C, D) Venn diagrams illustrating the overlap of (C) up-regulated and (D) down-regulated DEGs between the two datasets. The intersection reveals a core set of 83 consistently up-regulated and 42 consistently down-regulated genes across independent studies, highlighting robust transcriptional alterations in atherosclerosis.

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  Figure 2. Weighted gene co-expression network analysis (WGCNA) identifies key modules associated with high-fat diet. (A) Sample clustering dendrogram. One outlier sample was identified and excluded from subsequent network construction to ensure robustness. (B) Analysis of network topology for various soft-thresholding powers. The left panel shows the scale-free topology fit index (R2), and the right panel shows the mean connectivity. The selected power of β = 3 was the lowest power at which the network approximated a scale-free topology (R2 > 0.9). (C) Hierarchical clustering dendrogram of genes. Genes are grouped into modules of highly co-expressed genes, with each branch and color representing one module. (D) Module-trait associations heatmap. Each row corresponds to a gene module, and each column corresponds to a clinical trait. The color intensity represents the correlation coefficient (from −1 to 1), with associated p-values in parentheses. The blue and turquoise modules showed the strongest significant positive correlation with the HFD trait. (E, F) Scatterplots of Gene Significance (GS) for HFD versus Module Membership (MM) in the (E) blue (correlation = 0.92, p < 1e − 200) and (F)…

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  Figure 3. Identification and validation of Capg as a key hub gene in adipose dysfunction. (A) Venn diagram illustrating the overlap between differentially expressed genes (DEGs) and genes from the key WGCNA modules, identifying a core set of candidate hub genes for further investigation. (B) Protein-protein interaction (PPI) network of the common hub genes identified in (A). Nodes represent proteins, and edges represent predicted functional associations. (C) The top five hub genes ranked by connectivity within the PPI network, as identified by the CytoHubba plugin. (D) Independent validation of CAPG mRNA expression in the GSE39549 dataset. CAPG levels were significantly upregulated in the HFD group compared to the ND group (*p < 0.05). The label “nd” (not determined) refers to samples where data was unavailable. (E) Western blot analysis confirming the upregulation of CAPG protein expression in differentiated mature adipocytes treated with 400 µM linoleic acid (LA) for 48 h, compared to the vehicle control.

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  Figure 4. Overexpression of CAPG enhances the proliferation of 3T3-L1 preadipocytes. (A) Western Blot analysis confirming the successful overexpression of CAPG in 3T3-L1 cells transduced with CAPG-encoding lentivirus (Capg-OE) compared to control lentivirus (Ctrl). The membrane was probed with an anti-Flag antibody. (B) Cell viability measured by CCK-8 assay over 2 days. CAPG overexpression significantly promoted cell proliferation compared to the control group (n = 6 biological replicates per group). Data are presented as mean ± SD. (C) Representative Western Blots showing protein levels of the proliferation marker Cyclin D1 and CAPG in Ctrl and Capg-OE groups. (D) Quantitative densitometric analysis of the Western Blots from (C) (n = 4 independent experiments). CAPG overexpression led to a significant upregulation of Cyclin D1 protein levels, consistent with the enhanced proliferation phenotype. Data in (B) and (D) were analyzed by Student’s t-test. * p < 0.05; *** p < 0.001.

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  Figure 5. CAPG overexpression promotes adipogenesis in 3T3-L1 cells. (A) Representative images of Oil Red O staining in control (Ctrl) and CAPG-overexpressing (Capg-OE) adipocytes on day eight of differentiation, visualizing lipid accumulation. (B) Quantitative analysis of the Oil Red O staining shown in (A) by elution and spectrophotometry (n = 3 independent experiments). (C) High-magnification (200×) microscopic fields of the Oil Red O staining from (A); scale bar = 100 µm. (D) Quantitative analysis of the lipid droplet-positive area from the microscopic images in (C) (n = 3 independent experiments). (E) Representative Western Blots analyzing the protein levels of CAPG and key adipogenic markers (PPARγ, adiponectin) in Ctrl and Capg-OE cells. (F–I) Densitometric quantification of the protein levels from (E) for (F) CAPG, (G) PPARγ, (H) PPARγ2, and (I) adiponectin (n = 6 independent experiments). Data are presented as mean ± SD. Statistical significance was determined by Student’s t-test. **p < 0.01; ***p < 0.001; ****p < 0.0001.

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  Figure 6. CAPG overexpression selectively promotes the secretion of specific pro-inflammatory cytokines. (A–C) Concentrations of pro-inflammatory cytokines (A) IL-6, (B) MCP-1, and (C) TNF-α in the cell culture supernatant of control (Ctrl) and CAPG-overexpressing (Capg-OE) 3T3-L1 adipocytes, as measured by ELISA. Data are presented as mean ± SD from three independent experiments (n = 3). Statistical significance was determined by Student’s t-test. *p < 0.05; **p < 0.01; ns, not significant.