In Situ Expression of Yak IL-22 in Mammary Glands as a Treatment for Bovine Staphylococcus aureus-Induced Mastitis in Mice

Abstract

Since the development of dairy farming, bovine mastitis has been a problem plaguing the whole industry, which has led to a decrease in milk production, a reduction in dairy product quality, and an increase in costs. The use of antibiotics to treat mastitis can cause a series of problems, which can bring a series of harm to the animal itself, such as the development of bacterial resistance and dramatic changes in the gut flora. However, the in vivo and in vitro antibacterial activity of yak Interleukin-22 (IL-22) and its application in mastitis caused by Staphylococcus aureus have not been reported. In this study, the mammary gland-specific expression plasmid pLF-IL22 of the yak IL-22 gene was constructed and expressed in MAC-T cells and mammary tissue of postpartum female mice. The coding region of the IL-22 gene in yaks is 573 bp, which can encode 190 amino acids, and the homology difference in the IL-22 gene in yaks is less than 30%, which indicates certain conservation. IL-22 is a hydrophilic protein with a total positive charge of four, the presence of a signal peptide, and the absence of a transmembrane domain. Sufficient expression of IL-22 effectively inhibited the high expression of inflammatory factors caused by Staphylococcus aureus, reduced the symptoms of mammary gland histopathology, and alleviated mastitis. Under the action of IL-22, the intestinal flora of mastitis mice also changed, the abundance of intestinal Bacilli, Prevotellaceae, and Alloprevotella in mice increased after treatment, and the pathogenic bacteria decreased. These findings provide new insights into the potential application of the yak IL-22 gene in the treatment of bovine mastitis in the future.

Keywords: IL-22; Staphylococcus aureus; anti-inflammatory; intestinal flora; mastitis.

Figure 1

Sequence analysis of yak IL-22. (A) Homology analysis of yak IL-22. (B) Phylogenetic tree of yak IL-22.

Figure 2

Molecular characteristics of yak IL-22 protein. (A) Amino acid sequence of IL-22 protein. Red text letters represent positively charged amino acids; green represents negatively charged amino acids; double solid lines represent hydrophobic residues. (B) Three-dimensional structure of IL-22 protein. (C) Prediction of IL-22 protein signaling peptide. (D) Prediction of IL-22 protein transmembrane structure. (E) Prediction of hydrophilicity of IL-22 protein.

Figure 3

Construction and antibacterial effect of pLF-IL22. (A) Plasmid construction map of pLF-IL22. (B) Overexpression of pLF-IL22 plasmid in MAC-T cells (n = 3). (C) RT-qPCR test of inflammatory factors expression in cell therapy (n = 3). (D) RT-qPCR test of inflammatory factors expression in the treatment of mastitis in mice (n = 6). (E) Protein contents of inflammatory cytokines in serum of mice (n = 6). Differences were considered significant at p < 0.05 (*). Differences were considered very significant at p < 0.01 (**).

Figure 4

Body weight changes of mice (n = 6). (A) Body weights of mice in each group at the time of two injections. (B) Weight differences of mice in each group. Differences were considered significant at p < 0.05 (*). Differences were considered very significant at p < 0.01 (**).

Figure 5

Pathology and anatomy of mammary glands in mice. (A) Anatomical observation of mammary glands in mice of each group. Red arrows indicate the mammary glands in mice. (B) Pathological observation of mammary glands in mice of each group. Red arrows indicate epithelial cell necrosis, black arrows indicate epithelial cell degeneration, and yellow arrows indicate secretions and inflammatory cells.

Figure 6

Abundance of gut microbiota in mice (n = 6). (A) The Venn diagram was made according to the OTU abundance table, and the existence of OTUs in each sample group was used to count each set. (B) Histogram of relative abundance of species at the class level. (C) Sample dilution curve. (D) The top 10 genera with the highest relative abundances were screened for species classification tree statistics.

Figure 7

Intestinal microbial diversity, LEfSe, and function prediction (n = 6). (A) PCoA score plot based on OTU level. (B) Shannon diversity index of intestinal bacteria among groups. Differences were considered very significant at p < 0.01 (**). (C) UPGMA clustering tree based on weighted UniFrac distance. (D) Linear discriminant analysis (LDA). (E) Results of taxonomic cladograms. (F) Prediction of intestinal flora function.