Genome-wide transcriptional profiling of peripheral blood leukocytes from cattle infected with Mycobacterium bovis reveals suppression of host immune genes

Abstract

Background: Mycobacterium bovis is the causative agent of bovine tuberculosis (BTB), a pathological infection with significant economic impact. Recent studies have highlighted the role of functional genomics to better understand the molecular mechanisms governing the host immune response to M. bovis infection. Furthermore, these studies may enable the identification of novel transcriptional markers of BTB that can augment current diagnostic tests and surveillance programmes. In the present study, we have analysed the transcriptome of peripheral blood leukocytes (PBL) from eight M. bovis-infected and eight control non-infected age-matched and sex-matched Holstein-Friesian cattle using the Affymetrix® GeneChip® Bovine Genome Array with 24,072 gene probe sets representing more than 23,000 gene transcripts.

Results: Control and infected animals had similar mean white blood cell counts. However, the mean number of lymphocytes was significantly increased in the infected group relative to the control group (P = 0.001), while the mean number of monocytes was significantly decreased in the BTB group (P = 0.002). Hierarchical clustering analysis using gene expression data from all 5,388 detectable mRNA transcripts unambiguously partitioned the animals according to their disease status. In total, 2,960 gene transcripts were differentially expressed (DE) between the infected and control animal groups (adjusted P-value threshold ≤ 0.05); with the number of gene transcripts showing decreased relative expression (1,563) exceeding those displaying increased relative expression (1,397). Systems analysis using the Ingenuity® Systems Pathway Analysis (IPA) Knowledge Base revealed an over-representation of DE genes involved in the immune response functional category. More specifically, 64.5% of genes in the affects immune response subcategory displayed decreased relative expression levels in the infected animals compared to the control group.

Conclusions: This study demonstrates that genome-wide transcriptional profiling of PBL can distinguish active M. bovis-infected animals from control non-infected animals. Furthermore, the results obtained support previous investigations demonstrating that mycobacterial infection is associated with host transcriptional suppression. These data support the use of transcriptomic technologies to enable the identification of robust, reliable transcriptional markers of active M. bovis infection.

Figure 1

Mean leukocyte cell population subset counts in control and M. bovis-infected animals (n = 8 each group). Error bars represent the standard error for each mean cell count estimate.

Figure 2

Hierarchical clustering dendrogram generated using the complete gene expression profiles for the M. bovis-infected and control animals. The dendrogram was generated from the complete gene expression dataset for each animal using the Euclidean distance metric. The division between the BTB and control animal groups was supported by a bootstrap value of 100%.

Figure 3

Sub-categories of the top ranking IPA-identified inflammatory response gene ontology (GO) category. The numbers of genes displaying increased and decreased relative expression for affects immune response, the top ranking subcategory, are shown. The number of differentially expressed genes within each functional subcategory is indicated.

Figure 4

Differential gene expression in the TLR signalling pathway. Genes within the TLR signalling pathway showing differential expression are highlighted in colour. Colour intensity indicates the degree of increased (red) or decreased (green) relative expression in the BTB group compared to the control animal group. A white colour indicates genes that were not differentially expressed and entities coloured grey represent microbial PAMPs.