Unraveling key transposable elements in pathogen-induced bovine mastitis through comparative in vivo and in vitro transcriptomic analysis

Abstract

Background: Bovine mastitis poses significant hazards to the yield and quality of dairy products, severely hindering the development of the dairy industry. Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) are well-established as two of the primary pathogens causing the disease. Transposable elements (TEs), occupying a notable proportion of livestock genomes, primarily function as regulatory elements modulating gene expression. Extensive studies have indicated that TEs contribute to transcriptional changes in the host during pathogen invasion. However, despite their potential significance, the key functional TEs associated with bovine mastitis remain unclear, highlighting the need to explore the critical roles of TEs in the immune processes of this disease.

Results: In this study, in vitro and in vivo mastitis models were established using bovine mammary alveolar cells (Mac-T cells) and Chinese Holstein cows, respectively. In vitro findings showed distinct expression profiles of genes and TEs in response to challenges posed by S. aureus and E. coli. Specifically, 1,750 differentially expressed genes (DE Genes) and 3,046 differentially expressed TEs (DE TEs) were identified in the S. aureus challenge, while 2,353 DE Genes and 22,259 DE TEs were identified in the E. coli challenge. TEs were found to regulate the expression of genes primarily within immune-related pathways, including IL-17 and HIF-1 signaling pathways. TE-gene-QTL regulatory networks were established, providing preliminary insights into the molecular genetic mechanisms of TE regulation. By integrating in vitro and in vivo data, we identified and further validated two TE instances from MER53/DNA transposon and MIRc/SINE families as stably activated and repressed transcriptional markers for S. aureus mastitis, respectively.

Conclusions: Our research underscores the potential regulatory roles of TEs in the pathogenesis of bovine mastitis and highlights their applicability as molecular markers for early diagnosis and prevention of this economically significant disease. Our study offers novel insights for the breeding and improvement of resistance to pathogen-induced mastitis in dairy cattle.

Keywords: Escherichia coli; Staphylococcus aureus; Bovine mastitis; Transcriptomics; Transposable elements.

Fig. 1

Scientific question addressed in this study. Specifically, whether TEs, in response to pathogen stimuli, modulate gene expression and thereby influence mastitis susceptibility in dairy cattle

Fig. 2

Differentially expressed genes in S. aureus and E. coli mastitis models. (A, B) PCA analysis of gene expression in S. aureus and E. coli challenges, respectively. (C, D) Volcano plots of gene expression changes in S. aureus and E. coli challenges, with top 10 genes labeled. (E, F) Heatmaps of DE Genes in S. aureus and E. coli challenges, respectively

Fig. 3

Differentially expressed TEs in S. aureus and E. coli mastitis models. (A, B) PCA analysis of TE expression in S. aureus and E. coli challenges, respectively. (C, D) Volcano plots of TE expression changes in S. aureus and E. coli challenges, with top 10 TEs labeled. (E, F) Heatmaps of DE TEs in S. aureus and E. coli challenges, respectively. (G, H) Violin plots showing fold changes of DE TEs from four TE clades in S. aureus and E. coli challenges, respectively

Fig. 4

Functional annotation of TE-associated DE Genes in S. aureus and E. coli mastitis models. (A, B) Venn diagrams showing classification statistics of DE Genes and DE TEs in S. aureus and E. coli challenges, respectively. (C, D) KEGG enrichment analysis of DE TE-associated genes (associated DE Genes) in S. aureus and E. coli challenges, respectively. (E, F) Network diagrams of associated DE Genes within the top 3 KEGG pathways, paired with corresponding DE TE families, in S. aureus and E. coli challenges, respectively

Fig. 5

Correlation analysis of paired DE TEs and DE Genes in S. aureus and E. coli mastitis models. (A, B) Bar charts of the classification statistics of DE TEs in S. aureus and E. coli challenges, respectively. In legend, ‘up-none associated’ refers to TEs that are upregulated but not associated with DE Genes; ‘up-associated’ refers to TEs that are upregulated and associated with DE Genes; ‘down-none associated’ refers to TEs that are downregulated but not associated with DE Genes; ‘down-associated’ refers to TEs that are downregulated and associated with DE Genes. (C, D) Scatter plots showing the correlation between paired expression levels (TPM) of associated DE TEs and associated DE Genes in the challenge group (right) and the corresponding control group (left) of S. aureus and E. coli challenges, respectively, with linear models fitting correlation curves. In legend, ‘down-down’ represents the pairs of downregulated genes with downregulated TEs; ‘down-up’ represents the pairs of downregulated genes with upregulated TEs; ‘up-up’ represents the pairs of upregulated genes with upregulated TEs. (E, F) Peak plots of expression abundance for representative TE-gene pairs in S. aureus and E. coli challenges, respectively. (G) Schematic diagram illustrating synergistic expression patterns observed between adjacent TEs and genes under pathogen stimulation

Fig. 6

QTL enrichment and TE-gene-QTL regulatory network in S. aureus and E. coli mastitis models. (A, B) QTL enrichment analysis of TE-associated DE Genes in S. aureus and E. coli challenges, respectively. *, p < 0.05; **, p < 0.01; ***, p < 0.001, as determined by permutation tests on the overlap between QTL and gene regions. (C) TE-gene-QTL network based on QTLs linked to the “Mastitis” traits in S. aureus challenge. SCC, somatic cell count; SCS, somatic cell score; CM, clinical mastitis

Fig. 7

Integrated analysis of DE TEs in S. aureus mastitis in vitro and in vivo. (A, B) Venn diagrams showing the numbers of expressed genes and TEs (TPM > 0.1) in cellular and individual level (top panel). Scatter plots showing the correlation between the expression levels (log2(TPM + 1)) of all genes and TEs in Mac-T cells and udder quarters upon S. aureus challenge (lower panel). (C, D) Upset plot showing the number of DE Genes and DE TEs in the three between-group comparisons. (E, F) Bar chart of the expression level (TPM) of two instances from MER53/DNA transposon and MIRc/SINE families in five groups. (G) Bar chart illustrating the expression levels (TPM) of MER53_dup4007 and MIRc_dup8902 in the milk somatic cell dataset. HC, healthy control cows; SM, cows with subclinical mastitis. *, p < 0.05; ***, p < 0.001, as determined by differential expression analysis compared to the respective healthy control group