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. 2021 Sep 20;22(1):37.
doi: 10.1186/s12863-021-00991-2.

The transcription factor reservoir and chromatin landscape in activated plasmacytoid dendritic cells

Ritu Mann-Nüttel  1 , Shafaqat Ali  1   2   3 , Patrick Petzsch  4 , Karl Köhrer  4 , Judith Alferink  2   3 , Stefanie Scheu  5
Affiliations

The transcription factor reservoir and chromatin landscape in activated plasmacytoid dendritic cells

Ritu Mann-Nüttel et al. BMC Genom Data. .

Abstract

Background: Transcription factors (TFs) control gene expression by direct binding to regulatory regions of target genes but also by impacting chromatin landscapes and modulating DNA accessibility for other TFs. In recent years several TFs have been defined that control cell fate decisions and effector functions in the immune system. Plasmacytoid dendritic cells (pDCs) are an immune cell type with the unique capacity to produce high amounts of type I interferons quickly in response to contact with viral components. Hereby, this cell type is involved in anti-infectious immune responses but also in the development of inflammatory and autoimmune diseases. To date, the global TF reservoir in pDCs early after activation remains to be fully characterized.

Results: To fill this gap, we have performed a comprehensive analysis in naïve versus TLR9-activated murine pDCs in a time course study covering early timepoints after stimulation (2 h, 6 h, 12 h) integrating gene expression (RNA-Seq) and chromatin landscape (ATAC-Seq) studies. To unravel the biological processes underlying the changes in TF expression on a global scale gene ontology (GO) analyses were performed. We found that 70% of all genes annotated as TFs in the mouse genome (1014 out of 1636) are expressed in pDCs for at least one stimulation time point and are covering a wide range of TF classes defined by their specific DNA binding mechanisms. GO analysis revealed involvement of TLR9-induced TFs in epigenetic modulation, NFκB and JAK-STAT signaling, and protein production in the endoplasmic reticulum. pDC activation predominantly "turned on" the chromatin regions associated with TF genes. Our in silico analyses pointed at the AP-1 family of TFs as less noticed but possibly important players in these cells after activation. AP-1 family members exhibit (1) increased gene expression, (2) enhanced chromatin accessibility in their promoter region, and (3) a TF DNA binding motif that is globally enriched in genomic regions that were found more accessible in pDCs after TLR9 activation.

Conclusions: In this study we define the complete set of TLR9-regulated TFs in pDCs. Further, this study identifies the AP-1 family of TFs as potentially important but so far less well characterized regulators of pDC function.

Keywords: ATAC-Seq; Gene expression analysis; Next generation sequencing; Plasmacytoid dendritic cells; TLR9; Transcription factors.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Expression of transcription factors in pDCs. A Expression of TFs in pDCs in at least one of the following conditions: naïve, CpG 2 h, 6 h or 12 h (n = 3 per condition). B Categorization of the expressed TFs according to Hu et al. [11]. C Number of expressed vs non-expressed genes per TF family of a TF class is plotted
Fig. 2
Fig. 2
RNA-Seq reveals significant TF expression changes after pDC activation. A Pearson correlation plot for samples used in RNA-Seq. pDCs (CD3−CD19−CD11c+CD11blowB220+SiglecH+CD317+) were sorted from BM-derived Flt3-L cultures of C57BL/6 N mice and cells were left either naïve or stimulated with CpG for 2 h, 6 h or 12 h. B Volcano plots showing global expression of genes in sorted pDCs at steady state and after 2 h, 6 h, and 12 h of CpG stimulation. TF genes with a |FC| > 2 and a p-value of < 0.05 corrected for the false discovery rate (FDR) were considered significantly differentially expressed and are marked in colour (red and blue). C Bar chart depicting number of DETFs that are up or down-regulated between the respective conditions (|FC| > 2, p < 0.05). D, E Venn diagrams displaying significantly up and down-regulated TF genes (p ≤ 0.05, |FC| ≥ 2) between stimulated pDCs vs naïve pDCs (D) and 12 h pDCs stimulated vs naïve, 2 h and 6 h stimulated pDCs (E). F Heatmap showing normalized expression values (cpm, count per million) of differentially expressed TF genes from (B) in pDCs at steady state and after 2 h, 6 h, and 12 h of CpG stimulation. Hierarchical clustering on rows with average linkage and the One minus Pearson correlation metric was performed
Fig. 3
Fig. 3
Gene Ontology analysis of CpG-dependent TFs. 661 CpG-dependent TFs (|FC| > 2, p < 0.05) were analysed by DAVID functional annotation to produce gene clusters (> 2 genes/cluster) corresponding to biological process (BP), molecular function (MF), and cellular component (CC) GO annotation terms. Those significantly associated with the TF gene list are plotted with the numbers of genes for each term along with the fold enrichment for each term. A few terms were excluded as being redundant or having wider meaning (Table S5). Abbreviations are as follows: casc = cascade; cyt = cytokine; horm = hormone; med = mediated; reg = regulation; rERs = response to endoplasmic reticulum stress; resp. = response; sig = signaling
Fig. 4
Fig. 4
pDC activation increases and decreases chromatin accessibility of thousands of regions. A Pearson correlation plot for samples used in ATAC-Seq. pDCs (CD3−CD19−CD11c+CD11blowB220+SiglecH+CD317+) were sorted from BM-derived Flt3-L cultures of C57BL/6 Nmice and cells were left either naïve or stimulated with CpG for 2 h (n = 2). B Genomic location distribution of open chromatin sites in naïve and CpG stimulated pDCs according to ATAC-Seq. Two biological replicates were used per condition, and results are shown for pooled samples per condition. C Number of differentially accessible peaks detected using DESeq2, comparing naïve to 2 h CpG stimulated pDCs, |FC| > 2 and p < 0.05. D Heatmap of normalized ATAC-Seq peak intensities (log2FC relative to the mean for each peak). Limited to peaks (16,607) that are condition-dependent with |FC| > 2 and p < 0.05 for at least one pairwise comparison of interest. E Differential motif analysis for cluster I and II from (D) using MEME Centrimo and the HOCOMOCO v11 motif database. Significant motifs were categorized into known TF families for visualization and interpretation
Fig. 5
Fig. 5
TFs show CpG-dependent expression and chromatin accessibility. A Number of differentially accessible peaks of genomic regions associated with TF genes detected using DESeq2 comparing naïve to 2 h CpG stimulated pDCs, |FC| > 2 and p < 0.05. B Heatmap of normalized ATAC-Seq peak intensities (log2FC relative to the mean for each peak) limited to 540 peaks from (A) that are condition-dependent with |FC| > 2 and p < 0.05 for at least one pairwise comparison of interest. C The bar graph depicts normalized expression values obtained from RNA-Seq and statistics calculated with edgeR. D, E Top panel presents screen shots from the ECR (evolutionary conserved regions) Browser web site of the respective indicated gene. Exonic regions are shown in blue, intronic regions in pink, UTRs in yellow, and CNS in red. Bottom panels present ATAC-Seq peaks in naïve and CpG stimulated (2 h) pDCs for the indicated genes visualized with IGV. The AP-1 motif within the promoter sequence of the Tcf4 gene is highlighted in (E)
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