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Mastitis is a common disease in the dairy industry that causes huge economic losses worldwide. Exosomes (carrying proteins, miRNA, lncRNA, etc.) play a vital role in the regulation of immune response. lncRNA can play a variety of regulatory roles by combining with protein, RNA, and DNA. The expression of mRNA and lncRNA in exosomes derived from bovine mammary epithelial cells infected by  S. aureus  is rarely understood. To explore this issue, RNA sequencing analysis was performed on exosomes derived from  S. aureus -infected and noninfected MAC-T cells. Analysis of the sequencing results showed that there were 186 differentially expressed genes, 431 differentially expressed mRNAs and 19 differentially expressed lncRNAs in the exosomes derived from  S. aureus -infected and noninfected MAC-T cells. By predicting lncRNA target genes, it was found that 19 differentially expressed lncRNAs all acted on multiple mRNAs in cis and trans. GO analysis revealed that differentially expressed genes and lncRNA target genes played significant roles in such metabolism (reactive oxygen species metabolic processes), transmembrane transport, cellular response to DNA damage stimulus, and response to cytokines. KEGG enrichment indicated that lncRNA target genes gathered in the TNF pathway, Notch pathway, MAPK pathway, NF-kappa B pathway, Hippo pathway, p53 pathway, reactive oxygen species metabolic processes, and longevity regulating pathway. In summary, all data indicated that differentially expressed gene, mRNA, and lncRNA in transcriptional profiling of exosomes participated in bacterial invasion and adhesion, oxidative stress, inflammation, and apoptosis-related signaling pathway. The data obtained in this study would provide valuable resource for understanding the lncRNA information in exosomes derived from dairy cow mammary epithelial cells and conduced to the study of  S. aureus  infection in dairy cow mammary glands.

Transcriptional Profiling of Exosomes Derived from Staphylococcus aureus-Infected Bovine Mammary Epithelial Cell Line MAC-T by RNA-Seq Analysis