Evaluation of biological mechanisms of artemisinin on bovine mammary epithelial cells by integration of network pharmacology and TMT-based quantitative proteomics

Abstract

The sesquiterpene lactone, artemisinin, is a primary component of the medicinal plant Artemisia annua L., which has anti-inflammatory, antibacterial and antioxidant activities. However, the potential effects of artemisinin on the mammary gland of dairy cows and the underlying molecular mechanisms remain unclear. Here, we utilized systematic network pharmacology and proteomics to elucidate the mechanism by which artemisinin affects milk production and the proliferation of bovine mammary epithelial cells (BMECs). Nineteen bioactive compounds and 56 key targets were identified through database mining. To delineate the mechanism of artemisia's activity, a protein-protein interaction network and integrated visual display were generated from bioinformatics assays to explore the relationships and interactions among the bioactive molecules and their targets. The gene ontology (GO) terms and kyoto encyclopedia of genes and genomes annotation suggested that the apoptotic process, cell division, p53 pathway, prolactin and PI3K-Akt pathways played vital roles in mammary gland development. Using proteomics analysis, we identified 122 up-regulated and 96 down-regulated differentially significant expressed proteins (DSEPs). The differentially significant expressed proteins had multiple biological functions associated with cell division, apoptosis, differentiation, and migration. Gene ontology enrichment analysis suggested that differentially significant expressed proteins may promote cell proliferation and regulate apoptosis in bovine mammary epithelial cells. Kyoto encyclopedia of genes and genomes pathway analysis indicated that several biological pathways, such as those involved in antigen processing and presentation, cell adhesion molecules and ribosomes, played significant roles in the effects of artemisinin on bovine mammary epithelial cells. These findings contribute to a comprehensive understanding of the mechanism by which artemisinin affects bovine mammary epithelial cells to improve mammary gland turnover by inducing cell proliferation and mammary gland development.

Keywords: artemisinin; bovine mammary; dairy cow; network pharmacology; proteomics.

FIGURE 1

Venn diagram showing intersection of 56 ART-related milk biosynthesis targets.

FIGURE 2

Gene ontology (GO) enrichment analysis of intersected targets. Top ten biological process (BP) terms, cellular component (CC) terms, and molecular function (MF) terms are shown as green, orange, and purple bars, respectively. The X-axis represents the gene count of the target, and Y-axis represents the GO category of the target gene.

FIGURE 3

KEGG enrichment analysis of intersected targets. The top 20 KEGG pathways with adjusted p < 0.05 were selected and presented in a bubble chart manner. The size of the bubble represents the number of targets enriched in the indicated pathway and the color of the bubble represents the p value of enrichment.

FIGURE 4

Construction of the compounds-targets-pathways network. The pink V’s represent artemisinin; the hexagons indicate active compounds, the triangular nodes represent KEGG pathways, the elliptical nodes indicate intersected targets. Lines in the figure represent the interaction between two nodes. Both node size and color are in ascending order according to degree.

FIGURE 5

Volcano plot showing significantly up- (red) or down-regulated (green) proteins between the artemisinin treatment group and the control group. The gray points are proteins whose expression levels did not change significantly. The abscissa shows multiples of difference (logarithmic transformation of 2), while the ordinate is significant difference (p value, logarithmic transformation of 10).

FIGURE 6

GO terms of the DSEPs in the artemisinin treatment group compared with the control group. The red bars represent up-regulated proteins, and the blue bars represent down-regulated proteins.

FIGURE 7

GO enrichment analysis of DSEPs in the artemisinin treatment group vs. the control group. (A) GO enrichment analysis of upregulated DSEPs. (B) GO enrichment analysis of downregulated DSEPs. The x-axis represents the GO terms, while the y-axis represents the enrichment ratio, which is the ratio of the number of DSEPs in the GO term to the number of all annotated proteins in the GO term. The greater the ratio, the greater the degree of enrichment in each category. The color of the bars is related to the p value: ***p < 0.001, **p < 0.01, and*p < 0.05.

FIGURE 8

KEGG pathway analysis for DSEPs in the artemisinin group compared to the control group. (A) Upregulated DSEPs and (B) downregulated DSEPs. The ordinate is the name of the KEGG metabolic pathway, and the abscissa is the number of proteins annotated to the pathway. The bars are color-coded according to KEGG pathways, and the length of each bar corresponds to the number of proteins annotated to the corresponding pathway.

FIGURE 9

The top eight KEGG pathways enriched in DSEPs. The X-axis represents the corresponding pathway enrichment score; the Y-axis represents the name of each pathway. The enrichment score is the ratio of the number of DSEPs in the pathway to the number of all annotated proteins in the pathway; a higher enrichment score indicates a higher degree of enrichment, and a larger diameter of the circle indicates a greater number of DSEPs.