Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro

BACKGROUND: Mycobacterium bovis, the causative agent of bovine tuberculosis, is an intracellular pathogen that can persist inside host macrophages during infection via a diverse range of mechanisms that subvert the host immune response. In the current study, we have analysed and compared the transcriptomes of M. bovis-infected monocyte-derived macrophages (MDM) purified from six Holstein-Friesian females with the transcriptomes of non-infected control MDM from the same animals over a 24 h period using strand-specific RNA sequencing (RNA-seq). In addition, we compare gene expression profiles generated using RNA-seq with those previously generated by us using the high-density Affymetrix® GeneChip® Bovine Genome Array platform from the same MDM-extracted RNA. RESULTS: A mean of 7.2 million reads from each MDM sample mapped uniquely and unambiguously to single Bos taurus reference genome locations. Analysis of these mapped reads showed 2,584 genes (1,392 upregulated; 1,192 downregulated) and 757 putative natural antisense transcripts (558 upregulated; 119 downregulated) that were differentially expressed based on sense and antisense strand data, respectively (adjusted P-value ≤ 0.05). Of the differentially expressed genes, 694 were common to both the sense and antisense data sets, with the direction of expression (i.e. up- or downregulation) positively correlated for 693 genes and negatively correlated for the remaining gene. Gene ontology analysis of the differentially expressed genes revealed an enrichment of immune, apoptotic and cell signalling genes. Notably, the number of differentially expressed genes identified from RNA-seq sense strand analysis was greater than the number of differentially expressed genes detected from microarray analysis (2,584 genes versus 2,015 genes). Furthermore, our data reveal a greater dynamic range in the detection and quantification of gene transcripts for RNA-seq compared to microarray technology. CONCLUSIONS: This study highlights the value of RNA-seq in identifying novel immunomodulatory mechanisms that underlie host-mycobacterial pathogen interactions during infection, including possible complex post-transcriptional regulation of host gene expression involving antisense RNA

Key Hub and Bottleneck Genes Differentiate the Macrophage Response to Virulent and Attenuated Mycobacterium bovis

Mycobacterium bovis is an intracellular pathogen that causes tuberculosis in cattle. Following infection, the pathogen resides and persists inside host macrophages by subverting host immune responses via a diverse range of mechanisms. Here, a high-density bovine microarray platform was used to examine the bovine monocyte-derived macrophage transcriptome response to M. bovis infection relative to infection with the attenuated vaccine strain, M. bovis Bacille Calmette–Guérin. Differentially expressed genes were identified (adjusted P-value ≤0.01) and interaction networks generated across an infection time course of 2, 6, and 24 h. The largest number of biological interactions was observed in the 24-h network, which exhibited scale-free network properties. The 24-h network featured a small number of key hub and bottleneck gene nodes, including IKBKE, MYC, NFKB1, and EGR1 that differentiated the macrophage response to virulent and attenuated M. bovis strains, possibly via the modulation of host cell death mechanisms. These hub and bottleneck genes represent possible targets for immuno-modulation of host macrophages by virulent mycobacterial species that enable their survival within a hostile environment

Global Gene Expression and Systems Biology Analysis of Bovine Monocyte-Derived Macrophages in Response to In Vitro Challenge with Mycobacterium bovis

peer-reviewedBackground Mycobacterium bovis, the causative agent of bovine tuberculosis, is a major cause of mortality in global cattle populations. Macrophages are among the first cell types to encounter M. bovis following exposure and the response elicited by these cells is pivotal in determining the outcome of infection. Here, a functional genomics approach was undertaken to investigate global gene expression profiles in bovine monocyte-derived macrophages (MDM) purified from seven age-matched non-related females, in response to in vitro challenge with M. bovis (multiplicity of infection 2:1). Total cellular RNA was extracted from non-challenged control and M. bovis-challenged MDM for all animals at intervals of 2 hours, 6 hours and 24 hours post-challenge and prepared for global gene expression analysis using the Affymetrix® GeneChip® Bovine Genome Array. Results Comparison of M. bovis-challenged MDM gene expression profiles with those from the non-challenged MDM controls at each time point identified 3,064 differentially expressed genes 2 hours post-challenge, with 4,451 and 5,267 differentially expressed genes detected at the 6 hour and 24 hour time points, respectively (adjusted P-value threshold ≤0.05). Notably, the number of downregulated genes exceeded the number of upregulated genes in the M. bovis-challenged MDM across all time points; however, the fold-change in expression for the upregulated genes was markedly higher than that for the downregulated genes. Systems analysis revealed enrichment for genes involved in: (1) the inflammatory response; (2) cell signalling pathways, including Toll-like receptors and intracellular pathogen recognition receptors; and (3) apoptosis. Conclusions The increased number of downregulated genes is consistent with previous studies showing that M. bovis infection is associated with the repression of host gene expression. The results also support roles for MyD88-independent signalling and intracellular PRRs in mediating the host response to M. bovis.Science Foundation Ireland (www.sfi.ie) Investigator grants (Nos: SFI/01/F.1/B028 and SFI/08/IN.1/B2038); Department of Agriculture, Fisheries and Food (www.agriculture.ie) Research Stimulus Grant (No: RSF 06 405); European Union Framework 7 (http://cordis.europa.eu/fp7) Project Grant (No: KBBE-211602-MACROSYS); Irish Research Council for Science, Engineering and Technology (IRCSET) funded Bioinformatics and Systems Biology PhD Programme (http://bioinfo-casl.ucd.ie/PhD)

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

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.This work was supported by Investigator Grants from Science Foundation Ireland (Nos: SFI/01/F.1/B028 and SFI/08/IN.1/B2038), a Research Stimulus Grant from the Department of Agriculture, Fisheries and Food (No: RSF 06 405) and a European Union Framework 7 Project Grant (No: KBBE-211602-MACROSYS). KEK is supported by the Irish Research Council for Science, Engineering and Technology (IRCSET) funded Bioinformatics and Systems Biology PhD Programme http://bioinfo-casl.ucd.ie/PhD

The number of significantly differentially expressed genes at each time point post-<i>M. bovis</i> challenge.

<p>The number of upregulated and downregulated genes in the <i>M. bovis</i>-challenged MDM relative to the control MDM at each time point are shown (adjusted <i>P</i>-value 0.05).</p

Principal component analysis for all individual control and <i>M. bovis</i>-challenged MDM at the 2 hour, 6 hour and 24 hour time points.

<p>Principal component (PC) 1 and PC2 are shown (accounting for 23.31% and 17.05% of the total variation, respectively). PCA was performed using data for all genes whose probes passed the data filtering process with Euclidean distance as the distance metric.</p

Differential gene expression associated with apoptosis 6 hours post-<i>M. bovis</i> challenge.

<p>Genes associated with apoptosis showing differential expression are highlighted in colour. Colour intensity indicates the degree of upregulation (red) or downregulation relative to the control MDM. Grey shading indicates genes that were not differentially expressed; white shading represents genes in the pathway not represented on the microarray.</p

Differential gene expression associated with intracellular pathogen recognition receptors 24 hours post-<i>M. bovis</i> challenge.

<p>Genes associated with intracellular PRR signalling showing differential expression are highlighted in colour. Colour intensity indicates the degree of upregulation (red) or downregulation relative to the control MDM. Grey shading indicates genes that were not differentially expressed; white shading represents genes in the pathway not represented on the microarray; viral PAMPs are shaded orange.</p

Differential gene expression in the TLR signalling pathway 2 hours post-<i>M. bovis</i> challenge.

<p>Genes within the TLR signalling pathway showing differential expression are highlighted in colour. Colour intensity indicates the degree of upregulation (red) or downregulation relative to the control MDM. Grey shading indicates genes that were not differentially expressed; white shading represents genes in the pathway not represented on the microarray; mycobacterial PAMPs are shaded orange.</p

Schematic depicting the experimental design used in the current study.

<p>MDM were cultured in 24-well tissue culture plates (2×10⁵ cells per well) and challenged with <i>M. bovis</i> (MOI 2∶1). RNA was extracted from <i>M.bovis</i>-challenged and non-challenged control MDM at three time points post-challenge: 2 hours, 6 hours and 24 hours. In addition, RNA was extracted from a 0 hour non-challenged control to assess potential non-experimental changes in gene expression. The MDM lysates from replicate tissue culture wells (shaded) were pooled for RNA extraction. Global gene expression for the control and <i>M. bovis</i>-challenged MDM was analysed using the Affymetrix® GeneChip® Bovine Genome Array.</p