The FOXP3+ Pro-Inflammatory T Cell: A Potential Therapeutic Target in Crohn's Disease

Abstract

Background & aims: The incidence of Crohn's disease (CD) continues to increase worldwide. The contribution of CD4⁺ cell populations remains to be elucidated. We aimed to provide an in-depth transcriptional assessment of CD4⁺ T cells driving chronic inflammation in CD.

Methods: We performed single-cell RNA-sequencing in CD4⁺ T cells isolated from ileal biopsies of patients with CD compared with healthy individuals. Cells underwent clustering analysis, followed by analysis of gene signaling networks. We overlapped our differentially expressed genes with publicly available microarray data sets and performed functional in vitro studies, including an in vitro suppression assay and organoid systems, to model gene expression changes observed in CD regulatory T (Treg) cells and to test predicted therapeutics.

Results: We identified 5 distinct FOXP3⁺ regulatory Treg subpopulations. Tregs isolated from healthy controls represent the origin of pseudotemporal development into inflammation-associated subtypes. These proinflammatory Tregs displayed a unique responsiveness to tumor necrosis factor-α signaling with impaired suppressive activity in vitro and an elevated cytokine response in an organoid coculture system. As predicted in silico, the histone deacetylase inhibitor vorinostat normalized gene expression patterns, rescuing the suppressive function of FOXP3⁺ cells in vitro.

Conclusions: We identified a novel, proinflammatory FOXP3⁺ T cell subpopulation in patients with CD and developed a pipeline to specifically target these cells using the US Food and Drug Administration-approved drug vorinostat.

Keywords: IBD; T Regulatory Cell; scRNA Sequencing.

Extended Data Fig. 1:. Distribution of marker genes and sample composition.

(A) Heatmap depicting the top 10 marker genes across all distinct eight clusters within human CD4⁺ cells. (B) Proportions of cell types per healthy individual or CD patient and (C) proportions of the respective samples contributing to the total number of each cell type.

Extended Data Fig. 2:. Sample clustering and composition of Treg subtypes.

(A) PCA plot depicting the sample distribution of healthy controls (circle) and CD patients (triangle). (B) Tregs belonging to clusters 1–4 were represented by both sexes in all tissue samples. However, cells from cluster 5 were predominantly present in sample GEX_RST10175. (C) UMAP of FOXP3-positive cells indicating patient ID.

Extended Data Fig. 3:. Comparison between cells classified as Tregs in our study and in a colorectal cancer study by Lee et al.

(A) DotPlot of all marker genes for each cluster defined by Lee et al. and our study (PMID: 32451460). (B) UMAPs indicating the successful harmonization of our data with the dataset generated by Lee and colleagues (C) The three key markers for Tregs (CD4, IL2RA, FOXP3) were plotted on the harmonized UMAP together and (D) separately. (E) The visualization of cells positive for all three Treg markers demonstrates the high overlap between Tregs in both studies.

Extended Data Fig. 4:

The top 10 up- and downregulated genes per Treg subpopulation.

Extended Data Fig. 5:. Most differentially expressed genes among Treg subtypes separated by sex.

(A) UMAPs highlighting the most differentially expressed genes in cells isolated from females and the corresponding dotplot. UMAPs display the minimum (gray) and maximum (red) expression of these differentially expressed genes within all Tregs. (B) UMAPs and dot plot of those genes in cells isolated from males. Overall, we detected only marginal differences when comparing both sexes.

Extended Data Fig. 6:. Pseudotemporal development of Tregs determined using monocle2.

(A) Using moncle2, four branch points and a bifurcating developmental trajectory were calculated, with (B) cluster 0 depicting the earliest (start) cluster.

Extended Data Fig. 7:. Trajectory interference determined using RNA-velocity.

RNA-velocity estimation as basis of trajectory interference. While the trajectory in cluster 1 is heterogeneous, a continuous transition from cluster 2 to cluster 3 and 4 was visualized in an unbiased manner using scVelo and the algorithms published by La Manno et al. (PMID: 30089906).

Extended Data Fig. 8:. Developmental trajectories of healthy Tregs into distinct Treg subpopulations in female CD patients.

(A) Trajectory interference indicating early (purple) and late (yellow) fates. (B) Pseudotemporal development of five distinct Treg subpopulations. (C) Heatmap depicting genes differentially expressed during pseudotemporal progression (q-val <0.1; blue: low expression, red: high expression). (D) The expression of highly regulated DEGs was depicted in independent graphs.

Extended Data Fig. 9:. Developmental trajectories of healthy Tregs into distinct Treg subpopulations in male CD patients.

(A) Early (purple) and late (yellow) fates of Tregs isolated from male individuals. (B) Pseudotemporal development of five distinct Treg subpopulations. (C) DEGs displayed in a heatmap (q-val <0.1; blue: low expression, red: high expression) and in independent graphs.

Extended Data Fig. 10:. Temsirolimus treatment only partially rescues the proinflammatory effect of TNFα-treated FOXP3⁺ cells in vitro.

(A) Multiple inflammation-associated factors and pathways were predicted to be affected by Temsirolimus treatment as suggested by ASGARD and displayed using Cytoscape. (B) Human PBMCs were differentiated into Tregs in vitro and cytokines (U: untreated; T: TNFα; 12,21: IL12 and IL21; T12,21: TNFα, IL12 and IL21) were added for 24 h to induce the expression of TRICs. Upon the treatment with Temsirolimus, qRT-PCR analysis revealed only a partial rescue. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Mann-Whitney test.

Extended Data Fig 11:. Co-culture of normal colon organoids with T-regs.

Human colon epithelial organoids were co-cultured alone (A), with Tregs (B), and with Tregs stimulated with TNFa (C). Whole-mount organoids were subjected to immunofluorescent staining for CD45 (red), ZO1 (green) and DAPI (blue).

Fig. 1:. scRNA-seq reveals cellular dynamics in Crohn’s disease.

(A) Terminal ileal biopsies were extracted from age- and sex-matched CD patients (sequenced samples: female n=3, male n=2) and healthy individuals (sequenced samples: female n=3, male n=3). CD4⁺ cells were purified via flow cytometry and analyzed by scRNA-seq. (B) UMAPs displaying eight distinct cell populations identified in healthy and CD samples. Pie charts indicate the proportion of cells originating from healthy (light blue) and CD (rose) biopsies per cell type. (C) Total numbers per cell type within the healthy (11,520 cells) and CD (8,686 cells) populations and their relative abundance (%) per group (Fischer’s exact test *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001). (D) PCA plot displaying the distinct expression patterns in healthy (circle) and CD (triangle) cells. Unknown and CD4^low populations were not included in this analysis. (E) Top 10 upregulated (red) genes per cell type. Log₂FC >1.0, padj <0.05.

Fig. 2:. Identification of unique Treg subpopulations in Crohn’s Disease.

(A) All FOXP3-expressing cells (teal; 1,573 cells) were identified and (B) re-clustered. 33.6% (529 cells) of these cells were detected in the healthy and 66.4% (1,044 cells) in the CD population. (C) Based on their expression patterns, FOXP3-expressing cells were divided into five distinct subpopulations following UMAP calculation. (D) The 25 most differentially expressed genes were determined within the five Treg subpopulations. (E) UMAPs displaying the minimum (gray) and maximum (red) expression of these differentially expressed genes within all Tregs.

Fig. 3:. Developmental trajectories of healthy Tregs into distinct Treg subpopulations in CD.

(A) Based on gene expression patterns, the developmental dynamics of Tregs was evaluated using trajectory interference, indicating early (purple) and late (yellow) fates. Initial state: red arrowhead. (B) Pseudotemporal development of Tregs considering five distinct subpopulations. (C) Heatmap depicting genes differentially expressed during pseudotemporal progression (q-val <0.1; blue=low expression, red=high expression). (D) A subset of highly regulated DEGs was depicted in independent graphs.

Fig. 4:. Tregs isolated from CD patients display a unique responsiveness to TNFα signaling.

(A) Genes upregulated in Tregs isolated from CD patients were compared to the Human Molecular Signatures Database (MSigDB). This analysis uncovered highly significant enrichment of TNFα signaling via the NF-κB pathway (MSigDB_Hallmark_2020). (B) CellChat revealed that Tregs display a particularly high incoming rather than outgoing interaction strength for the TNF signaling pathway network. (C) This signaling towards Tregs is mainly mediated by Th17 (red), Th1 (blue) and effector memory cells (orange). (D) Role of the respective CD4⁺ cell types as senders, receivers, mediators, and influencers in TNFα signaling (color intensity corresponds to interaction strength; light orange: low involvement, dark brown: high involvement). (E) Genes upregulated in FOXP3⁺ T cells isolated from CD lesions were compared to genes induced in a publicly available microarray dataset of human Tregs treated with TNFα in vitro and compared to untreated control cells (GSE18893). A significant overlap was observed between both datasets (Fisher’s exact test, p=0.0095; Odds ratio: 3.65). (F) Ten Treg-specific genes induced in Crohn’s (TRICs) were defined by overlapping genes upregulated in Tregs compared to all other cell populations with genes upregulated in CD Tregs. (G) To model the induction of TRICs in vitro, we isolated CD45RA⁺ naïve T cells from healthy donors and differentiated them into FOXP3⁺ Tregs. These cells were treated with designated cytokines for 48 h. (H) In three independent experiments (each n=3), a substantial induction of TRICs was confirmed after TNFα treatment using qRT-PCR.

Fig. 5:. CD Tregs can be targeted via vorinostat treatment.

(A) Using the ASGARD package, the most promising drugs to reverse expression patterns of CD Tregs were determined. (B) As predicted by ASGARD and displayed using Cytoscape, vorinostat treatment impacts multiple inflammation-associated proteins and pathways, including chemokine, NF-κB and TNFα signaling. (C) Publicly available gene expression profiles from Tregs isolated from mice with a Treg-specific Hdac1 or (D) Hdac2 deletion (GSE139480), were downloaded to perform GSEA using FOXP3⁺ cells from our own dataset. HDAC-dependent genes were significantly enriched in CD Tregs. (E) Human PBMCs were differentiated into Tregs in vitro and different cytokines were added for 24 h to induce the expression of TRICs (U: untreated; T: TNFα; 12,21: IL12 and IL21; T12,21: TNFα, IL12 and IL21). Afterwards, cells were treated with vorinostat for 24h. qRT-PCR analysis revealed that the upregulation of TRICs upon cytokine treatment was rescued by the addition of vorinostat. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Mann-Whitney test.

Fig. 6:. Vorinostat rescues the suppressive function of inflammatory FOXP3⁺ T cells in vitro.

(A) To perform in vitro suppression assays, CD25⁻⁻ cells were isolated from the same patients as CD4⁺ naïve T cells and frozen until CD4⁺ naïve T cells were successfully differentiated to Tregs and treated with TNFα and/or vorinostat. Tregs were washed and cultured in 4 different dilutions (1:1, 1:2, 1:4 and 1:8) with 5,000 CD25⁻ responder cells. Assessment of proliferation revealed that the suppressive capacity of TNFα-treated Tregs was reduced but could be rescued by HDACi in four independent experiments (each n=3, One-way ANOVA, multiple testing, Tukey, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001). (B) Human colon epithelial organoids were co-cultured with Tregs. Whole-mount organoids were subjected to immunofluorescent staining for Ki67 (red), ZO-1 (green) and DAPI (blue) in duplicates in two independent experiments. Scale bar: 10μm. (C) Gene expression of MKI67, TJP1, MLKL2, RIPK3 and LGR5 in co-cultured cells was evaluated using qRT-PCR. (D) Cytokine levels in supernatants of co-cultured cells was determined using a Human Cytokine 71-Plex Discovery Assay (Eve Technologies). *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Mann-Whitney test.