Alpha-Tocopherol Modulates Transcriptional Activities that Affect Essential Biological Processes in Bovine Cells

Abstract

Using global expression profiling and pathway analysis on α-tocopherol-induced gene perturbation in bovine cells, this study has generated comprehensive information on the physiological functions of α-tocopherol. The data confirmed α-tocopherol is a potent regulator of gene expression and α-tocopherol possesses novel transcriptional activities that affect essential biological processes. The genes identified fall within a broad range of functional categories and provide the molecular basis for its distinctive effects. Enrichment analyses of gene regulatory networks indicate α-tocopherol alter the canonical pathway of lipid metabolism and transcription factors SREBP1 and SREBP2, (Sterol regulatory element binding proteins), which mediate the regulatory functions of lipid metabolism. Transcription factors HNF4-α (Hepatocyte nuclear factor 4), c-Myc, SP1 (Sp1 transcription factor), ESR1 (estrogen receptor 1, nuclear), and androgen receptor, along with several others, were centered as the hubs of transcription regulation networks. The data also provided direct evidence that α-tocopherol is involved in maintaining immuno-homeostasis through targeting the C3 (Complement Component 3) gene.

Keywords: ESR1; bovine cells; gene regulation; lipid metabolism; α-tocopherol.

Figure 1.

Alpha-tocopherol induces inhabitation of cell proliferation in Madin-Darby bovine kidney (MDBK) epithelial cells. A1–A4) Histogram plot of flow cytometry analysis of MDBK cells sorted by their DNA content in cells treated with 0, 10, 20 and 40 μM alpha-tocopherol respectively. (S: S-phase-DNA or the synthesis phase of the cell cycle. Synthesis occurs in the S phase and chromosomes are duplicated) B) Quantized cell population. G1/G0: cells in G1/G0 cell cycle phases; S: cells in S cell cycle phase.

Figure 2.

Western blotting of proteins. This figure is representative of two experiments. Equal amount of protein from different samples were separated by SDS PAGE 4 to 20% polyacrylamide gradient gels and was transferred to a membrane for Western blotting. The graphic represent quantitation from two Western blots.

Figure 3.

The top 10 most significant pathways, based on the overrepresentation analysis (P < 0.05) induced by α-topopherol treatment.

Figure 4.

GeneGO Pathway Maps. The top scored map (map with the lowest P-value) based on the enrichment distribution sorted by ‘Statistically significant Maps’ set with the lowest P-value and ordered by –log10 of the P-value of the hypergeometric distribution: Regulation of lipid metabolismregulation of lipid metabolism through LXR, NF-Y and SREBP pathway. Experimental data is linked to and visualized on the maps as thermometer-like figures. Up-ward thermometers have red color and indicate up-regulated signals and down-ward (blue) ones indicate down-regulated expression levels of the genes.

Figure 5.

Representative biological network generated using the Analyze Networks Transcription regulation Algorithm. Up-regulated genes are marked with red circles and down-regulated genes are marked with blue circles. The network is centered with NF-κB and ESR1. All other transcription factors are shown in the left panel. All the symbols in the network are listed in Supplement Figure S1.

Figure 6.

GeneGo process networks: representation of the most significant biological process networks induced by α-tocopherol, sorted by statistically significant Networks, ordered by –log¹⁰ of the P-value of the hypergeometric distribution.

Figure 7.

The representative network of the most relevant biological networks that is unique to up-regulated networks using the Analyze Networks Transcription regulation Algorithm. This is a variant of the shortest paths algorithm with relative enrichment and relative saturation of networks with canonical pathways. Key network objects include ESR1, C3, Erk1/2 (shown in blue rectangles). Large orange rectangle highlights the transcription factors.

Figure 8.

The representative networks of the most relevant biological networks that are unique to down-regulated networks using the Analyze Networks Transcription regulation Algorithm. This is a variant of the shortest paths algorithm with relative enrichment and relative saturation of networks with canonical pathways. The figure shows three (green, purple and red) merged down-regulated networks.