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. 2016 Aug 22:6:31603.
doi: 10.1038/srep31603.

Immune cell-specific transcriptional profiling highlights distinct molecular pathways controlled by Tob1 upon experimental autoimmune encephalomyelitis

Alessandro Didonna  1 , Egle Cekanaviciute  1 , Jorge R Oksenberg  1 , Sergio E Baranzini  1
Affiliations

Immune cell-specific transcriptional profiling highlights distinct molecular pathways controlled by Tob1 upon experimental autoimmune encephalomyelitis

Alessandro Didonna et al. Sci Rep. .

Abstract

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system characterized by focal lymphocytic infiltration, demyelination and neurodegeneration. Despite the recent advances in understanding MS molecular basis, no reliable biomarkers have been identified yet to monitor disease progression. Our group has previously reported that low levels of TOB1 in CD4(+) T cells are strongly associated with a higher risk of MS conversion in individuals experiencing an initial demyelinating event. Consistently, Tob1 ablation in mice exacerbates the clinical phenotype of the MS model experimental autoimmune encephalomyelitis (EAE). To shed light on Tob1 molecular functions in the immune system, we have conducted the first cell-based transcriptomic analysis in Tob1(-/-) and wildtype mice upon EAE. Next-generation sequencing was employed to characterize the changes in gene expression in T and B cells at pre- and post-symptomatic EAE stages. Remarkably, we found only modest overlap among the different genetic signatures, suggesting that Tob1 may control distinct genetic programs in the different cytotypes. This hypothesis was corroborated by gene ontology and global interactome analyses, which highlighted specific cellular pathways in each cellular subset before and after EAE induction. In summary, our work pinpoints a multifaceted activity of Tob1 in both homeostasis and disease progression.

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Figures

Figure 1
Figure 1. Tob1 ablation increases B cell proliferative capacity.
WT or Tob1-KO splenocytes were stimulated with 5 μg/mL lipopolysaccharides (LPS) for 3 days or left unstimulated. Afterwards, cells were fixed and the B cell population immunostained with a PE-conjugated anti-B220. Cell proliferation analysis was then performed by flow cytometry as described in the Materials and Methods section. Tob1-KO B cells show a statistically significant increase in cell proliferation either (a) before stimulation or (b) after stimulation as compared to WT cells. Results are shown as mean ± SE and derive from three independent experiments, each one using 3 mice per genotype. **P ≤ 0.01, one-tailed T test.
Figure 2
Figure 2. Cytokine and immunoglobulin profiling in Tob1-KO and WT B cells.
B cells were isolated by negative selection from the spleens of Tob1 KO or WT mice and then stimulated with 5 μg/mL lipopolysaccharides (LPS) for 3 days or left unstimulated. Conditioned media were subsequently collected and probed for the levels of (a) interleukin 6 (Il-6), (b) Il-10, (c) IgG and (d) IgM. No significant differences were detected in the secretion of these molecules between WT and KO cells, before or after LPS stimulation. Results are shown as mean ± SE and derive from at least 3 animals per genotype.
Figure 3
Figure 3. Clustering analysis of immune cell genetic signatures from Tob1-KO and WT mice upon EAE.
(a) Plot of the first 2 principal components (PC1 on the x-axis and PC2 on the y-axis) calculated from the expression values of the genes with the highest variance that are expressed in CD4+ T cells (in yellow), CD8+ T cells (in green) and B cells (in blue) isolated from Tob1-deficient and wildtype mice at different EAE stages (0, 5 and 15 dpi). Two main clusters can be recognized, corresponding to B and T cell lineages. (b) Unsupervised hierarchical clustering of expression values for the same genes and samples as in panel a. Each row represents a gene while each column corresponds to a different sample. The distances between genes or samples are calculated using Spearman correlation. The different datasets cluster first by cytotype, forming three main groups that correspond to CD4+, CD8+ and B cell populations. Within each cluster, the influence of disease course prevails on genotype for CD4+ T cells and B cells while the opposite trend is observed for CD8+ T cells.
Figure 4
Figure 4. T and B cells respond differently to Tob1 ablation in terms of differentially expressed genes.
The number of significant genes that were up- (in blue) or down-regulated (in red) in Tob1-knockout mice compared to wildtype animals was plotted for each cell population at the different EAE stages. At baseline, CD4+ and CD8+ T cells are characterized by only down-regulated genes while B cells show the opposite tendency with most of the significant genes being upregulated. In contrast, at 5 and 15 dpi, the majority of significant genes is upregulated for the three cytotypes.
Figure 5
Figure 5. Limited overlap exists among CD4+, CD8+ and B cell molecular signatures.
(a) Venn diagrams showing the overlap among the nominally significant genes (Tob1-KO vs WT) of the three immune cell populations at 0, 5 and 15 dpi. (b) Venn diagrams showing the overlap among the nominally significant genes identified at the three time points analyzed for each immune cell population. In both cases, the number of genes shared by different cytotypes or disease stages is limited.
Figure 6
Figure 6. Global interactome analysis identifies biologically relevant gene networks for each immune cell population.
(a) Significant networks (Z score > 3) enriched in genes with nominal P values from CD4+ T cell comparisons (Tob1-KO vs WT) at different EAE stages. One significant network was identified at 0 and 5 dpi while two networks were found at 15 dpi. The analysis was performed using Cytoscape and jActive module plugin. (b) Significant networks for CD8+ T cells. Similar to CD4+ T cells, also CD8+ T cells are defined by one network at 0 and 5 dpi and two networks at 15 dpi. (c) Significant networks for B cells. Only one network was identified at baseline while no network passed the cutoff for the other two EAE time points.
Figure 7
Figure 7. The long non-coding RNA GM3764 is dramatically upregulated in Tob1-KO CD4+ T cells and promotes cell proliferation.
(a) The expression levels for the lncRNA GM3764 were analyzed by quantitative RT-PCR in CD4+, CD8+ and B cells at baseline (0 dpi). The data were normalized to GAPDH levels which served as internal control. A 16-fold increase in GM3764 expression was detected in Tob1-KO CD4+ T cells while a 2-fold increase was identified in KO B cells. No difference was instead reported in CD8+ T cells. All experiments were carried out in triplicate and the average values are plotted. (b) GM3764 or GFP were overexpressed in 3T3 cells and, after 48 hours, cell growth was assessed by XTT assay. A statistically significant increase in cell proliferation was measured in lncRNA-expressing cells compared to control. Results are presented as mean ± SE and derive from 4 independent transfections. (c) Phospho-ERK1/2 levels were probed in GM3764 overexpressing 3T3 cells for 48 hours. A statistically significant increase in phospho-ERK1/2 levels was detected in lncRNA-overexpressing cells compared to control. Endogenous actin levels served as internal loading control. Results are presented as mean ± SE and derive from 3 independent transfections. **P ≤ 0.01, one-tailed T test.
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