Distinct Gene Regulatory Pathways for Human Innate versus Adaptive Lymphoid Cells

Abstract

Innate lymphoid cells (ILCs) serve as sentinels in mucosal tissues, sensing release of soluble inflammatory mediators, rapidly communicating danger via cytokine secretion, and functioning as guardians of tissue homeostasis. Although ILCs have been extensively studied in model organisms, little is known about these "first responders" in humans, especially their lineage and functional kinships to cytokine-secreting T helper (Th) cell counterparts. Here, we report gene regulatory circuitries for four human ILC-Th counterparts derived from mucosal environments, revealing that each ILC subset diverges as a distinct lineage from Th and circulating natural killer cells but shares circuitry devoted to functional polarization with their Th counterparts. Super-enhancers demarcate cohorts of cell-identity genes in each lineage, uncovering new modes of regulation for signature cytokines, new molecules that likely impart important functions to ILCs, and potential mechanisms for autoimmune disease SNP associations within ILC-Th subsets.

Figure 1. Transcriptome analysis of primary human tonsillar ILCs and Th cells

(A) Strategy for iILC1 and ILC3 sorting. (B) Supervised PCA of genes with most variable expression among iILC1, ILC3, Th1, Th17, and blood cNK cell replicates (top 15%). (C) Plot comparing the fold change of ILC3 and iILC1 to the fold change of Th17 and Th1 depicts transcripts differentially expressed among ILCs and Th subsets. Colored circles highlight transcripts expressed at least two fold higher in a single tonsillar subset compared with the other three subsets. Colored circles with black borders denote transcripts that are shared by both an ILC and Th subset with expression >2 fold higher than cells of their respective lineage. (D) Transcripts shared by ILC subsets that were increased by two fold compared to Th subsets and vice versa. (E) Heatmaps highlighting the average expression of selected transcripts that were differentially expressed in each cell type as shown in panels C and D. Color coding at the left of each heatmap designates the categories of cell type-restricted expression patterns, retaining colors shown in panels C and D. (F) The highest scoring IPA network generated from transcripts differentially expressed in ILCs versus Th cells, as in panel D. Transcripts represented in red were upregulated in ILCs versus Th cells at least two-fold in microarray data, and those in green were similarly downregulated. Darker colors indicate greater fold changes among upregulated or downregulated transcripts. See also Figure S1.

Figure 2. Unique and shared enhancers in human ILC and Th subsets

(A) The stacked bar graph shows numbers of active enhancers that were either unique (gray) or shared (red shades) by the indicated number of cell types. The pie graphs depict cell type distributions for unique (bottom) or shared (top) active enhancers. (B) Fold change expression of genes (+ SD) located most proximally to enhancers uniquely active in the indicated cell type. For each panel, expression in the indicated cell type was compared to average expression in the other three subsets. *Denotes statistical significance (p<0.01) using a one-way anova. (C) UCSC Genome Browser views of the human IFNG locus, showing tracks of DNAse-, ATAC- and H3K27ac ChIP-seq data for the indicated cell types, displayed as reads per million (RPM) values. For human Th1 cells, published DNAse-seq data are shown (GSE29692). A track for mammalian sequence conservation is provided at the bottom. Colored bars above tracks represent statistically significant called peaks. Known IFNG regulatory regions (CNSs) are boxed and categorized by cell type restriction in their activities. (D) Activity status (poised versus off) in other cell types for enhancers that were designated as uniquely active in a given subset. Boxes highlight the subset of enhancers that are off in other cell types. See also Figure S2 and Tables S1-S3.

Figure 3. Enriched TF motifs in ILC versus Th regulomes

(A) Fold change p-values for enrichment of TF motifs comparing enhancers that are differentially active in ILC versus Th cells. (B) Heatmap showing the log p-values for enrichment of TF motifs in enhancers that exhibit augmented H3K27ac in one cell type versus the other three. (C) Relative expression of selected members for TF families identified in panel B. (D) Heat maps (left) showing the binding of BATF or IRF4 in GM12878 B cells (http://genome.ucsc.edu/ENCODE/) at enhancers (+ 2 kb) identified as ILC3- or Th17-enriched. The right bar graphs quantify numbers of enhancers that bind BATF and/or IRF4 in the indicated cell types. (E) UCSC Genome Browser view of human IL22 (top) as described in Figure 2C. The cell type specificity of each boxed enhancer is shown at the top. The middle tracks denote sites of TF binding in GM12878 cells. The bottom tracks show data for BATF and IRF4 in mouse Th17 cells (Li et al., 2012) at conserved enhancer regions. See also Figure S3.

Figure 4. Super-enhancer distribution in human ILC and Th subsets

(A) Rank order of increasing H3K27ac enrichment at enhancer loci for each ILC–Th subset. Red dots denote SEs that are uniquely called in each cell type and selected genes associated with these SEs. (B) SE distributions. Stacked bar shows active enhancers that are unique (gray) or shared by the indicated number of cell types (red shades). Pie graphs depict distributions for unique SEs (bottom) or those shared by two cell types (top). (C) Relative expression levels of genes within 30 kb of cell type-specific SEs. Statistical significance (paired T-test): *p≤ 0.05. (D) Venn diagram showing unique and shared categories of SEs with a selected set of associated genes highlighted. See also Figure S4.

Figure 5. Novel SE-regulated loci

(A) UCSC Genome Browser view of RPM-normalized H3K27ac data for the CD300LFSE with relative expression for CD300LF in each cell type shown at the right. Red bar denotes designated SE. (B) Flow cytometric analysis for CD300f protein (encoded by the CD300LF gene) on tonsillar ILC3s and iILC1s. A small CD300f⁺ population within iILC1s may represent converting ILC3s. (C) UCSC Genome Browser view of RPM-normalized H3K27ac data for the IL17A/F-SE with relative expression for IL17A/F in each cell type shown at the right. (D) UCSC Genome Browser view of RPM-normalized H3K27ac data for the IL22/26-SE with relative expression for IL22/26 in each cell type shown at the right. Arrows represent interactions tested by 3C assays. (E) Luciferase reporter assays for enhancer activity in two regions from the IL22/26-SE. See panel D for locations of tested elements. Control vectors were the Tcrb enhancer (Eβ) for Jurkat T cells and the SV40 enhancer for HepG2 cells. Experiments were performed in triplicate. Shown are mean values (+ SD) for fold change versus a vector containing only the minimal SV40 promoter, normalized by Renilla luciferase. Statistical significance (one-way anova): *p< 0.05, **p< 0.01, ***p< 0.001. (F) 3C assays in Th1 and Th17 cells from human blood. The assays test relative crosslinking efficiency of the IL22 promoter region (labeled “0” in D) and selected enhancer or control regions within or flanking the SE, as designated in panel D.

Figure 6. Autoimmune-associated SNPs found in ILC–Th super-enhancers

(A) Proportion of total SNPs associated with autoimmunity or non-B cell cancers found in SEs from the four ILC-Th subsets. Statistical significance (permutation analysis): **p≤ 0.01. (B) Number of autoimmune SNPs in called SEs divided into categories based on cell type distributions. (C) UCSC Genome Browser view of two loci associated with an ILC3-specific (IL1R1/IL2R1, top) or an ILC-Th SE region (ASAP1/FAM49B, bottom) with the autoimmune disease SNPs highlighted. Right panels show predicted TF motifs potentially disrupted by the autoimmune SNP (UC, ulcerative colitis; MS, multiple sclerosis).