Fig 2: The adaptive immunity in spleens of the colorectal PC model. (A) FACS gating strategy for spleen T/B cells. Debris and doublets were removed, and then the spleen T/B cells were assessed as DAPI-CD45+CD90.2+/B220+. The levels of T/B cells and CD8+/CD4+ T cells were also measured. (B-C) The levels of spleen T/B cells at different time points. Six-week-old mice were intraperitoneally injected with MC-38 cells. Then the splenocytes were isolated for flow cytometric analysis of T/B cells (B) and CD8+/CD4+ T cells (C). Shown are representative images. Data are mean± s.e.m. (n=3, *P< 0.05, student's t-test)

Fig 3: UTX alters gene expression in virus-specific CD8+ T cells(A) An illustration of the approach. WT and UTX-deficient P14+CD8+ T cells were introduced into the separate hosts, followed by CD4 depletion and infection with LCMV-A22. Donor cells from 3–4 mice were isolated by FACS at day 15 for H3K27me3 CUT&RUN or UTX CUT&Tag analyses or isolated at day 22 for RNA-seq analyses.(B) EdgeR analysis of RNA-seq data showing genes with significantly changed expression (FDR < 0.05; log2 fold change > |1.0|), comparing genes significantly downregulated in Utx-/- donor P14+ T cells (purple) to those upregulated (green). RNA-seq data are derived from FACS donor cells from 3–4 recipient mice per group.(C) GSEA of effector genes, ranked according to their relative expression in WT and Utx-/- cells. The genes in this gene set are known to be expressed in CTLs, but not naive cells.(D) Genes showing significant differences in expression were subjected to GOrilla analysis followed by REVIGO analysis. The analysis identified several biological processes that are predicted to be significantly altered between WT and Utx-/- T cells based on differential gene expression.(E) Isolated cells were subjected to H3K27me3 CUT&RUN analysis. The anti-H3K27me3-bound DNA fragments were eluted, sequenced, and quantified across the genome. The graph depicts the relative change in Utx-/- H3K27me3 density (log2 fold change) compared to WT for individual genes that were grouped based on changes in Utx-/- gene expression (RNA-seq in B). H3K27me3 changes are shown for genes having equal (black), significantly downregulated (purple), or significantly upregulated (green) RNA expression in Utx-/- P14s. The H3K27me3 CUT&RUN data are from four recipients per group.(F) UCSC genome browser images of normalized H3K27me3 tracks at the Gzma, Thy1, Cd9, Crtam, Ubash3b, and Sema7a loci, showing mean values from four independent replicates of WT (black) or Utx-/- (red). The heavy bars depict regions with significantly enriched peaks of H3K27me3 in UTX-deficient P14 cells, compared to WT cells.(G–I) UTX CUT&Tag was performed on WT CD8+ T cells at day 0 (n = 2) and day 15 post-infection (n = 4) and at day 15 for Utx-/- (KO) cells (n = 2).(G and H) The average profile of UTX coverage is plotted based on normalized read counts for all UTX peaks of enrichment that occur at transcription start sites (TSSs; G) or enhancers (H). Enhancers were annotated based on published ATAC-seq datasets (Beltra et al., 2020). Start and stop define the boundary of the UTX peaks. Line colors indicate the profile for WT uninfected P14 (D0; light blue), WT at day 15 of LCMV infection (dark blue), or Utx-/- at day 15 (black).(I) The pie graph depicts the proportion of UTX binding at TSSs, enhancers, active enhancers, and other locations (neither TSS nor enhancer) that are within 20 kb of TSSs. Active enhancer annotation was based on published H3K27ac datasets (Yao et al., 2019).(J) H3K27me3 CUT&RUN changes were correlated with UTX binding at day 15 post-infection at genes showing reduced expression in Utx-/- T cells. Utx-/- misregulated genes were categorized as UTX bound or unbound, then contrasted for the percentage of these genes that experienced increased H3K27me3 in Utx-/- P14 cells.(K and L) All H3K27me3 peaks of enrichment that failed to overlap with UTX peaks (UTX-unbound; K) are illustrated for comparison to UTX peaks near genes with reduced expression in Utx-/- cells (UTX-bound; L). The average profile of H3K27me3 coverage is plotted based on normalized read counts for WT (red) or Utx-/- P14 (dark red) samples.(M and N) The UTX-bound H3K27me3 profiles in (L) were further subdivided into UTX peaks that overlap TSSs (M) or putative enhancers (N).(O and P) Profiles of ATAC-seq normalized reads (Beltra et al., 2020) identify the open chromatin status of enhancers in “progenitor exhausted„ (Texprog1; O) or intermediate exhausted (Texint; P) T cells. These putative enhancers were subdivided based on overlap with UTX peaks of enrichment (UTX-bound; light blue profile) or peaks lacking UTX association (unbound; black profile).(Q) The profile of H3K27ac ChIP-seq normalized reads (Yao et al., 2019) demonstrates enhancer activation status at regions that overlap with UTX binding (pink) compared to enhancers not bound by UTX (black).See also Figure S6 and Tables S1, S2, S3, and S4.

Fig 4: UTX demethylase activity is not required for effector CD8+ T cell function during chronic infectionWT, UTX-KI (catalytic dead knockin), and UTX-KO P14+CD8+ T cells were introduced into the same recipients, followed by CD4 depletion and infection with LCMV-A22. At day 8 post-infection, splenic donor P14T cells were analyzed for surface marker expression, transcription factor levels, and cytokine expression.(A) Illustration of the approach.(B) The three donor P14 T cell populations and host CD8+ T cells were identified by surface expression Ly5a, Ly5b, and Thy1.1.(C) Frequency of each donor P14 group among all donor CD8+Ly5a+ P14 T cells in spleen. Lines connect pairs of WT, UTX-KI, and UTX-KO P14T cells present in each recipient.(D) Histogram plots and gMFI for the transcription factors T-bet, Eomes, Tox, Tcf1, and Bcl2.(E and F) The fraction of donor P14 T cells producing granzyme (E) and the gMFI of granzyme expression among granzyme-positive cells (F).(G and H) The fraction of donor cells making IFN? (G) and the gMFI among IFN?-positive cells (H).(I) The distribution of IFN?+ (left) and IFN?- (right) donor cell populations after re-stimulation with GP33–41 peptide in an ICCS assay. The left graph shows the distribution of donor cells among the IFN?+ cells; the right graphs shows the distribution of donor cells that failed to make IFN?.(J) The histograms show several activation and inhibitory receptors expressed by IFN?+ donor cells.(K) The surface expression of Ly108 and CD69 on each donor cell population was used to identify Texprog1, Texprog2, Texint, and Texterm subsets.(L) Distribution of the four developmental stages of exhaustion for donor cell populations. Each circle represents 1% of the total population.Data show one experiment with five recipient mice. Samples from the five recipient mice were concatenated to generate histograms. Significance was determined by a paired Student’s t test (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001).See also Figure S7.

Fig 5: TGFβ pathway is the key inhibitory signal for dermal adipogenesis in the WISF model. (A) ClusterGVis analyses of the wound centre, edge and distal skin RNAseq data identified four gene clusters with distinct expression dynamics. Left panel: the number and expression pattern of genes in each cluster. Right panel: GO analyses of the relevant biological processes for each cluster. (B) Heatmap showing the relative expression of indicated genes. (C–H) Mature adult mice were administrated i.d. with TGFBR inhibitor (SB) or DMSO during the course of WISF, and wounds were collected at w.d. 24. (D) Bodipy staining of skin wounds. Zoom‐in images cropped from the edge area are shown on the right. Scale bar, 1 mm. (E, F) HE staining of the centre scar tissue (E), and quantified results showing the thickness of skin dermis is shown in F (n = 5/group). Scale bar, 200 μm. (G) Immunostaining of COL1A1 (green), THY1 (red), DPP4 (blue) and DAPI (white). Scale bar, 200 μm. (H) qRT‐PCR analysis of key fibrotic or adipocyte‐related genes as indicated (n = 3 ~ 4/group). All error bars indicate mean ± SEM. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.