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MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model

Nathan Lawless, Timothy A. Reinhardt, Kenneth Bryan, Mike Baker, Bruce Pesch, Duane Zimmerman, Kurt Zuelke, Ted Sonstegard, Cilona O'Farrelly, John D. Lippolis, David J. Lynn
G3 2014 v.4 no.6 pp. 957-971
Holstein, Streptococcus uberis, biochemical pathways, bovine mastitis, cattle, chemokines, disease resistance, gene expression, gene expression regulation, genes, high-throughput nucleotide sequencing, inflammation, innate immunity, interferons, mammary glands, messenger RNA, metabolism, microRNA, milk, models, monocytes, phenotype, plate count, somatic cell count, transcription factors
Bovine mastitis is an inflammation-driven disease of the bovine mammary gland that costs the global dairy industry several billion dollars per annum. Because disease susceptibility is a multi-factorial complex phenotype, a multi-omic integrative biology approach is required to dissect the multilayered molecular networks involved. Here, we report such an approach, using next generation sequencing combined with advanced network and pathway biology methods to simultaneously profile mRNA and miRNA expression at multiple time-points (0, 12, 24, 36 and 48h) in both milk and blood FACS-isolated CD14+ monocytes from Holstein Friesians infected in vivo with Streptococcus uberis. The course of the infection was monitored through bacterial counts, somatic cell count (SCC) and several other parameters. More than four billion reads were sequenced and analysed to profile mRNA expression in the milk and blood isolated monocyte (MIMs and BIMs) samples. In MIMs, 2,056 and 1,721 genes were up- and down-regulated, respectively, at, at least, one time-point following S. uberis infection. In BIMs, however, we also observed a subtle but significant response to infection. 83 genes were up-regulated in BIMs by 48hpi. Pathway analysis revealed that up-regulated genes in MIMs were significantly enriched for roles in inflammatory and other innate immune pathways (e.g. TLR, NLR and RIG-I signalling), while down-regulated genes were significantly associated with metabolic pathways. InnateDB network analysis of differentially expressed (DE) genes revealed that contextual hubs were highly enriched for roles in innate immunity (FDR < 1.16E-12). The majority of the top 20 contextual hubs were well known transcriptional regulators of innate immunity (e.g. CREBBP, EP300, IRF1, IRF9, JUN, NFKB1, REL, RELA, STAT1, STAT3). Genes up-regulated in BIMs showed a significant association with interferon and chemokine signalling. Analysis of the miRNAseq data revealed that 26 miRNAs were DE in response to infection in MIMs. Only four miRNAs were found to be DE in BIMs. Simultaneous profiling of miRNA and mRNA expression enabled us to computationally correlate expression of miRNAs with their potential mRNA targets. Pathway analysis revealed that predicted targets of down-regulated miRNAs were highly enriched for roles in innate immunity (FDR < 3.4E-8) in particular TLR signalling, while up-regulated miRNAs preferentially targeted genes involved in metabolism. We conclude that during S. uberis infection miRNAs are key amplifiers of monocyte inflammatory response networks and repressors of several metabolic pathways.