Experiments were performed with age-matched CREB^fl/fl, VAV^creCREB^fl/fl , and Foxp3^creCREB^fl/fl mice (all C57BL/6). Foxp3^creCREB^fl/fl mice were generated by crossing CREB-flox mice (20) with C57BL/6 Foxp3-IRES Cre mice (provided by T. Bopp, University of Mainz, Germany). Foxp3^cre-CREB^fl/fl mice were used as controls (denoted as CREB^fl/fl ). Foxp3^CreROSA^RFP mice were provided by T. Bopp University of Mainz and crossed with our CREB^fl/fl mice. Rag2^-/- (C57BL/6) mice were provided by A. Schippers (Uniklinik RWTH Aachen, Germany). All the mice were bred in our animal facility and kept under standardized conditions.

To induce transfer colitis, Rag2^-/- mice were adoptively transferred 2 x 10⁶ CD4⁺ CD25^- T cells. Animals were sacrificed as soon as a significant loss of weight was measurable. The spleen and mesenteric lymph nodes (mLNs) were harvested for further analysis. One part of the colon was fixed in formalin for histological scoring and the other part was fixed in RNAlater (Qiagen, Germany) for subsequent mRNA analysis. For soluble ST2 (sST2) treatment, the mice received 100 µg mouse sST2 (produced by the VIB Protein Core facility, Belgium, and provided by R. Beyaert, VIB-UGent Center for Inflammation Research, Belgium), three times/week by intraperitoneal means (i.p). The control group received PBS i.p. For IL-10R treatment, the mice received 500 µg anti-IL-10R antibody (1B1mAB) (kindly provided by Prof. Edgar Schmitt, University of Mainz, Germany) or IgG control AK (Rat IgG kappa) i.p. once a week during the first 3 weeks.

Initially, 4 µm paraffin sections from the fixed colon were cut serially, mounted onto glass slides, and deparaffinized. The colon sections were stained with hematoxylin and eosin by the Core Facility (IZKF) of the RWTH Aachen University. Blinded histological scoring was performed using a standard microscope, based on the JLS method as described previously (21, 22). Each colon section was scored for the four general criteria: severity, degree of hyperplasia, degree of ulceration, if present, and percentage of area involved. A subjective range of 1–3 (1 = mild, 2 = moderate, 3 = severe) was used for the first three categories. Severity: Focally small or widely separated multifocal areas of inflammation limited to the lamina propria were graded as mild lesions (1). Multifocal or locally extensive areas of inflammation extending to the submucosa were graded as moderate lesions (2). If the inflammation extended to all layers of the intestinal wall or the entire intestinal epithelium was destroyed, lesions were graded as severe (3). Hyperplasia: Mild hyperplasia consisted of morphologically normal lining epithelium that was at least twice as thick (length of crypts) as adjacent or control mucosa. Moderate hyperplasia was characterized by the lining epithelium being two or three times the normal thickness, cells were hyperchromatic, numbers of goblet cells were decreased, and scattered individual crypts developed an arborizing pattern. Severe hyperplastic regions exhibited a markedly thickened epithelium (four or more times normal thickness), marked hyperchromasia of cells, few to no goblet cells, a high mitotic index of cells within the crypts, and numerous crypts with an arborizing pattern. Ulceration was graded as: 0 = no ulcer, 1 = 1–2 ulcers (involving up to a total of 20 crypts), 2 = 1–4 ulcers (involving a total of 20–40 crypts), and 3 = any ulcers exceeding the former in size. A 10% scale was used to estimate the area involved in the inflammatory process. 0 = 0%, 1 = 10%–30%, 2 = 40%–70%, 3 = >70%.

Single cell suspensions were isolated from spleens and lymph nodes (LNs) [peripheral lymph nodes (pLNs) and mLNs] using cell strainers and erythrocytes were lysed with lysis buffer. To obtain immune cells from the lungs, tissue was excised into small pieces and digested with 0.1% collagenase in DPBS for 1hr. The digested fraction was passed through a 40μm nylon strainer and rinsed with DPBS. The flow through was centrifuged and the cell pellet was lysed using RBC lysis buffer. The cell pellet was used for the flow cytometric analysis. Colons were retrieved from the mice and rinsed with a cannula with PBS+0.5%BSA. Afterwards, the colons were excised into small pieces and placed in a digestive medium containing RPMI (10mL), collagenase V (0.85mg/mL), collagenase D (1.25mg/mL), dispase (1mg/mL) and DNase (30μg/mL) and incubated for 45 minutes at 37°C with gentle shaking. The digested fraction was passed through a 40 μm nylon strainer and the flow-through was collected and centrifuged to obtain a pellet. Percoll gradient centrifugation was performed by using 35% Percoll. The cell pellet obtained was lysed using RBC lysis buffer and was used for further analysis. The livers were retrieved from the mice. The gall bladders were removed and the livers were excised into small pieces and placed in a digestive medium containing RPMI without FCS (3mL), 1.25mg/mL collagenase D, and 30μg/mL DNase. The fraction was incubated for 45 minutes and digestion was stopped by adding PBS+0.5% BSA+2mM EDTA and homogenized using a syringe. The digested fraction was passed through a 100μm nylon strainer and the flow-through was centrifuged. The pellet obtained was used for the Percoll gradient centrifugation using 35% Percoll. The cell pellet obtained after the Percoll gradient centrifugation was lysed using RBC lysis buffer and was used for the flow cytometric analysis.

CD4 T-cells (T_effector cells) were isolated from the spleens of wild-type mice. The cells were labeled with eFluor 660 proliferation dye from Thermo Fischer according to the manufacturer’s instructions. After the labeling, the cells were stimulated with plate-coated anti-CD3 (10µg/mL, eBioscience, Germany) and soluble anti-CD28 (1µg/mL) (eBioscience) in the presence of CD4+CD25+ cells from either wild-type or Foxp3^creCREB^fl/fl mice in different ratios (1:0, 1:0.5, 1:0.75, and 1:1) for 3 days. After 3 days of stimulation, the cells were analyzed using flow cytometric analysis.

Magnetic Activated Cell Sorting (MACS)-isolated CD4⁺CD25^- T cells (2x10⁶ per mL) were incubated with plate-coated anti-CD3 (10µg/mL, eBioscience, Germany) and soluble anti-CD28 (1µg/mL) (eBioscience, Germany). T_H0 cells were left without exogenous cytokines, and 5 ng/mL TGF-β was added to induce T_reg differentiation.

For surface staining, single cell suspensions were stained with anti-CD4, anti-CD3, anti-CD8, anti-B220, anti-CD25, CD45, anti-GL-7, anti-ICOS, anti-ST2, anti-Nrp1, and anti-PD-1 (all from eBioscience, Germany). For intracellular staining of CREB, Foxp3, CTLA-4, Helios, GATA3, T-bet, and RORγt, cells were fixed and permeabilized with a FOXP3 staining buffer set (Thermo Fischer, eBioscience, Germany) following the manufacturer’s instructions and stained with respective antibodies (eBioscience, Germany) for 30 min. Intracellular cytokines were stained with anti-IFN-γ-Alexa 647 (eBioscience, Germany) and anti-IL-17-Alexa 488 (BD, USA), and IL-10-APC (eBioscience, Germany) after PMA (30nM) and Ionomycin (1.5µM) (both Sigma-Aldrich, USA) re-stimulation in the presence of GolgiPlug/GolgiStop (BD Biosciences, USA). A daily calibrated FACS-Canto II flow cytometer (Becton Dickinson, MountainView, CA, USA) was used to perform the phenotypic analysis. Lymphocytes were gated by forward (FSC), side scatter (SSC), and CD3, CD4, and B220 expression. A figure exemplifying the gating strategies is provided in the Supplementary Materials ( Supplementary Figure 6 ). For data analysis FCS-Express 4.0 Research Edition (DeNovo software Glendale, CA, USA) and FlowJo version 10 were used.

RLM cells carrying a stable pGL3-TSDR-FoxPro luciferase plasmid were kindly provided by Jochen Huehn (HZI Braunschweig, Germany). Cells were transfected with the pcDNA-CREB plasmid or pcDNA. Cells were left to rest overnight before luciferase activity was measured by using the Dual-Glo Luciferase Assay System (Promega, USA).

Total RNA from isolated T cells and colon tissue was isolated using the RNeasy Mini Kit (Qiagen, Germany). cDNA was then generated from 200 ng total RNA using the RevertAid H Minus First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, USA) according to the manufacturer´s instructions. RT-PCR was performed using the SYBR Green PCR kit (Eurogentec, Germany) and data were acquired with the ABI Prism 7300 RT-PCR system (Applied Biosystems/Life Technologies, Germany). Each measurement was set up in duplicate. After normalization to the endogenous reference control gene ß-actin for mice, the relative expression was calculated.

CD4⁺CD25⁺Nrp1⁺ T_regs were sorted by FACS. Genome-wide transcriptome analyses of Foxp ^creCREB^fl/fl and CREB^fl/fl T_regs were performed in independent triplicate using Gene Chip^® Mouse Gene 2.0 arrays (Affymetrix, Santa Clara, CA, USA). Total RNA extraction was carried out using the RNeasy Micro Kit (Qiagen, Germany) according to the manufacturer’s protocol and then quantified (Nanodrop). RNA quality was assessed using the RNA 6000 Nano Assay with the 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA). Samples for the Gene 2.0 arrays were prepared and hybridized to the arrays according to the Affymetrix WT Plus Kit manual. Briefly, for each sample, 100 ng of total RNA was reverse-transcribed into cDNA using a random hexamer oligonucleotide tagged with a T7 promoter sequence. After second-strand synthesis, double-strand cDNA was used as a template for amplification with T7 RNA polymerase to obtain antisense cRNA. Random hexamers and dNTPs spiked out with dUTP were then used to reverse-transcribe the cRNA into single-stranded sense-strand cDNA. The cDNA was then fragmented with uracil DNA glycosylase and apurinic/apyrimidic endonuclease 1. The fragment size was checked using the 2100 Bioanalyzer and ranged from 50 to 200 bp. Fragmented sense cDNA was biotin-end-labeled with TdT and the probes were hybridized to the Gene 2.0 arrays at 45°C for 16h with 60 rpms. Hybridized arrays were washed and stained on a Fluidics Station 450 (program: FS450 0002) and scanned on a GeneChip^® Scanner 3000 7G (both Affymetrix). Raw image data were analyzed with Affymetrix^® Expression Console™ Software (Affymetrix, USA), and gene expression intensities were normalized and summarized with a robust multiarray average algorithm (23). Transcripts that were expressed differently more than 1.5-fold with a raw p-value lower than 0.05 between the sample groups were categorized as regulated. A enrichment analysis for Wiki pathways was performed using WebGestalt (24). For the enrichment analysis only, genes that changed at least 1.5-fold with a p-value lower than 0.05 between Foxp3^creCREB^fl/fl and CREB^fl/fl samples were taken into consideration.

For all the methylation analyses, cells from male mice were used. Genomic DNA was prepared from FACS-sorted T_conv cells (CD4⁺CD25^-) and T_reg cells (CD4⁺CD25⁺Nrp1⁺) from CREB^fl/fl and Foxp3^creCREB^fl/fl mice and subsequently converted by bisulfite according to the manufacturer’s instructions (DNeasy Blood & Tissue Kit, Qiagen; EZ DNA Methylation-Lightning Kit, Zymo Research, USA). Pyrosequencing of the Treg cell-specific demethylated region (TSDR) (chromosome position X:7583950-7584149, genome assembly GRCm38.p6) was performed as described previously (25).

Omni-transposase-accessible chromatin assay using sequencing (ATAC-seq) was performed according to (26, 27) with minor modifications. Prior to transposition, dead cells were removed by centrifugation (800 rpm, 4 min, 4°C). The transposition reaction was conducted with 7.5 μL Tagment DNA Enzyme 1 (TDE1) for 60 min at 37°C. Pre-amplification was conducted with NEBNext Ultra II Q5 Master Mix and Nextera PCR Primers (5 cycles). Quantitative PCR amplification was conducted with NEBNext Ultra II Q5 Master Mix, Nextera PCR Primer, and SYBR Gold to determine the number of additional cycles. PCR amplification of additional cycles was the same as for pre-amplification. PCR fragments were purified with Qiagen MinElute PCR Purification Kit and library concentration and quality were determined using an Agilent High Sensitive DNA Kit and TapeStation, respectively. ATACseq libraries were sequenced on the Illumina NextSeq 500 Platform with 75 bps paired-end reads in duplicate. ATAC-seq libraries were trimmed with Trim Galore (parameters -q 30 –paired –trim1) and aligned to the mouse genome (mm9) using Bowtie2 (28) (parameters -X2000 –no-mixed –no-discordant). Duplicate fragments were removed, and reads were filtered for alignment quality of >Q30 using samtools (29). Next, we used MAC2 (30) to perform peak calling (parameters: nomodel, nolambda, keep-dup auto, call-summits). Transcription factor footprinting and differential activity was performed using HINT-ATAC as described in Li et al. (27).

Total IgG and IgE were measured from sera using the Ready-Set-Go ELISA system (affymetrix: eBioscience, USA). IL-10 was determined in cell supernatants using mouse IL-10 ELISA Ready-SET-GO! (2nd Generation) (Thermo Fisher Scientific, USA), according to the manufacturer’s instructions.

All data are presented as mean ± standard error (SEM). Data were tested for normality using the Shapiro–Wilk normality test. Differences between two groups were evaluated using two-tailed unpaired or paired (if indicated) Student’s t-tests. A two-tailed Mann–Whitney test was used if data were not normally distributed. One-way ANOVA was performed if there are more than two groups. Measurements were taken from distinct samples. All statistical analysis and subsequent graphics generation were performed using GraphPad Prism versions 7.0 and 8.0 (GraphPad Software, USA). A p-value <0.05 was statistically significant.

The animal study was approved by the regional government authorities and animal procedures were performed according to German legislation for animal protection. Permission for the projects was granted by the Regierungspräsident/LANUV Nordrhein-Westfalen (81-02.04. 2017.A393).

The ATAC-Seq and microarray raw datasets have been deposited in GEO under the accession codes GSE157693 and GSE157933. All data that support the findings of this study are available within the article and the Supplementary Material . All other data, including raw data used in each figure, will be provided upon reasonable request to the corresponding author.

CREB is a transcriptional activator and has been found to critically stabilize Foxp3 expression (31). It is therefore widely accepted that CREB promotes FoxP3 expression in T_regs (32–34). To verify this hypothesis in vivo, we generated mice with a Foxp3-specific knockout of CREB (Foxp3^creCREB^fl/fl ). To our surprise, these mice showed enhanced numbers of CD25⁺/Foxp3⁺ positive T_regs in the thymus ( Figures 1A, D ), spleen ( Figures 1B, D ), and pLN ( Figures 1C, D ). Splenic T_regs showed no altered expression of Nrp1, PD-1, CTLA4, and ICOS ( Supplementary Figures 1A, B ). There was also no convincing different expression of T_h lineage transcription factors GATA3 and RORyT and T-bet in CD4⁺Foxp3⁺ cells within different organs ( Supplementary Figures 2A–E ). However, Foxp3^creCREB^fl/fl mice displayed lower Foxp3 expression in T_regs on the single cell level ( Figures 1E, F ), which can be explained by the fact that CREB directly activates the TSDR (31) ( Figure 1G ). To verify Cre expression in the Foxp3-Cre mice, we crossed Foxp3^creCREB^fl/fl mice with Cre-inducible reporter mice (ROSA^{R FP}) and examined reporter gene expression in lymphocytes. RFP expression was confined to CD4⁺CD25⁺ cells, which is important for excluding cell extrinsic side-effects ( Figures 1H, I ).

We further used Foxp3^creCREB^fl/fl ROSA^{R FP} mice to assess the percentages of T_regs in non-lymphoid organs. While we did not observe differences in liver tissue, we found a particularly marked upregulation of T_reg percentages within the lungs and colons of Foxp3^creCREB^fl/fl ROSA^{R FP} mice compared to Foxp3^creROSA ^RFP mice ( Figures 1J–L ) and enhanced absolute numbers of T_regs in the colons of Foxp3^creCREB^fl/fl ROSA^{R FP} ( Supplementary Figure 7B ). This prompted us to analyze whether CREB expression in T_regs differs in different tissues. We could not find an association between high tissue-dependent CREB expression and the effects of CREB deficiency on T_reg percentages; however, we found a high expression of CREB in murine colonic T_regs ( Supplementary Figure 8 ).

To test whether lower Foxp3 expression affects the suppressive capacity of CREB-deficient T_regs, we co-cultured CREB^fl/fl T_regs and Foxp3^creCREB^fl/fl T_regs with anti-CD3 and anti-CD28 stimulated WT CD4⁺ cells. Surprisingly, Foxp3^creCREB^fl/fl T_regs revealed an increased capacity to reduce CD4⁺ T cell proliferation ( Figures 2A, B ). These data suggest that deletion of CREB, despite reducing Foxp3 expression per cell, enhances the function of T_regs. In addition, the expression of Helios was enhanced ( Figure 2C ) and bisulfite sequencing revealed a demethylated TSDR ( Figure 2D ), which suggests a stable and suppressive phenotype (35). In conclusion, despite the reduction of Foxp3 levels per cell, CREB deficiency leads to stable and functional T_regs in vitro.

To understand why CREB-deficient T_regs are suppressive despite reduced Foxp3 expression, we performed a whole transcriptome analysis (Affymetrix HTA2 arrays) of flow-sorted (CD4⁺CD25⁺Nrp-1⁺) Foxp3^creCREB^fl/fl and CREB^fl/fl T_regs ( Supplementary Figure 3A ) and appropriate wild-type mice because, at the time of this analysis, the Foxp3^CRECREB^fl/fl ROSA^{R FP} mice were not yet available. Using a fold-change of 1.5 and a p-value of less than 0.05, we found 111 downregulated and 122 upregulated genes in the Foxp3^creCREB^fl/fl compared to the CREB^fl/fl T_regs, and among them, IL-10 and IL-13 were the two most differentially regulated in the Foxp3^creCREB^fl/fl T_regs ( Figure 3A ). KEGG pathway analysis revealed an enrichment of differentially regulated genes in pathways that are associated with Th2 cytokines, such as asthma, Th2 and Th2 cell differentiation, and cytokine-cytokine receptor interaction pathways ( Figure 3B ). Higher Il13 and Il10 mRNA expression in Foxp3^creCREB^fl/fl T_regs could be further confirmed by RT-qPCR ( Figures 3C, D ). CD4⁺CD25⁺Foxp3⁺ cells also showed enhanced IL-10 protein levels after 3 days of CD3/CD28 stimulation, as assessed by flow cytometry ( Figures 3E, F ). In vitro T_reg differentiation with TGF-β revealed a reduced capacity of Foxp3^creCREB^fl/fl T cells to differentiate towards Foxp3⁺ cells, while IL-10 expressing cells within Foxp3⁺ cells were enhanced ( Figure 3G ). Furthermore, IL-10 cytokine expression of TGF-β−stimulated Foxp3^creCREB^fl/fl T cells measured by ELISA was enhanced, as was Il13, Il5, and Il10 mRNA expression, which suggests that CREB deficiency in T_regs induces a Th2-biased phenotype ( Figures 3H-L ). Beyond cytokines, Il1r1 (ST2) showed enhanced expression on the microarray. ST2, the receptor of IL-33, is preferentially expressed on colonic T_regs, where it promotes T_reg function and adaptation to the inflammatory environment. It provides a necessary signal for T_reg-cell accumulation and maintenance in inflamed tissues, and it was shown to regulate IL-10-expressing T_regs in the gut (8). In addition, IL-33 has been identified as a major interleukin in asthma pathology (36). ST2 was highly expressed in the Foxp3^creCREB^fl/fl T_regs, which was confirmed by flow cytometry ( Figures 3M, N ). Moreover, the whole transcriptome analysis also revealed an upregulated expression of CREM in Foxp3^creCREB^fl/fl T_regs and qRT-PCR also showed tendentially enhanced CREM expression in Foxp3^creCREB^fl/fl T_regs ( Figure 3O ). In conclusion, these data suggest that CREB deletion induces ST2⁺ T_regs. This finding led us to investigate the protein expression of ST2 within different organs in Foxp3^creROSA^RFP and Foxp3^creCREB^fl/flROSA^RFP mice. ST2 expression was clearly enhanced in T_regs in the thymus, spleens, mesenteric lymph nodes, lungs, and colons of these mice ( Figures 3P–T ).

Since ST2⁺T_regs also play a protective role in intestinal mucosal inflammation (8), we performed a transfer of Foxp3^creCREB^fl/fl T cells (CD4+CD25-) or appropriate CREB^fl/fl T cells (CD4+CD25-) into lymphopenic Rag2^-/- mice. This usually results in the development of colitis within 5 weeks. Strikingly, the transfer of Foxp3^creCREB^fl/fl T cells did not result in the expected weight loss ( Figure 4A ) and the recipient mice displayed decreased intestinal inflammation ( Figures 4B, C ). Furthermore, there was a significant decrease of Il6, Tnfa, Il17a, and Ifng, along with a non-significant trend towards decreased Il1b in the gut ( Figure 4D ) and reduced IFN-γ production. There was also a trend towards reduced IL-17A in CD4⁺ T cells in the mLNs ( Supplementary Figure S4E–G ). Limitations include the absence of IL-6 and TNFα protein data due to the limited availability of the tissue. The experiment was repeated with CD4+CD25- T cells from Foxp3^creROSA^{R FP} and Foxp3^creCREB^fl/fl ROSA^{R FP} mice into Rag2-/- mice and with CD4+CD25- cells from CREB^fl/fl and VAV^creCREB^fl/fl mice into Rag2-/- mice, with the same results. The transfer of CD4+CD25- T cells from Foxp3^creCREB^fl/fl ROSA^{R FP} mice ( Figures 5A–G ) and from VAV^creCREB^fl/fl prevented the development of colitis ( Supplementary Figure 11 ) and resulted in enhanced accumulation of RFP+ T_regs in different organs ( Figures 5A–G ). Interestingly, RFP+ T_regs also accumulated in the liver, while we did not find a difference in the RFP expression in the Foxp3^creCREB^fl/fl ROSA^{R FP} mice under steady state conditions.

ST2⁺ T_regs are protective in intestinal inflammation (8), and,in addition, they are Th₂ biased and release IL-10 (37). To decipher whether Foxp3^creCREB^fl/fl T cells prevent colitis through IL-10 production and/or ST2 expression, we performed an adoptive transfer colitis experiment with anti-IL10R antibodies or recombinant soluble ST2 (sST2). sST2 acts as a decoy for IL-33 and inhibits its biological activity (38). The blockade of IL-10 signaling induced colitis in the formerly resistant Foxp3^creCREB^fl/fl T cell-recipient mice ( Figures 6A–C ), while the ST2 blockade had no effect on disease progression ( Supplementary Figure 4 ).

To analyze whether CREB deletion alters chromatin accessibility at different promoters and enhancers, we performed ATAC-seq in CREB^fl/fl and Foxp3^creCREB^fl/fl T_regs. We observed a decrease in open chromatin around CREB and CREM motifs in the Foxp3^creCREB^fl/fl mice, which indicates loss of binding activity of these transcription factors in these cells ( Figure 7A ). The Il1rl1 (ST2) region showed significant differences in open chromatin around the original and an alternative promoter in T_regs from the Foxp3^creCREB^fl/fl mice, while canonical CRE motifs, which are 8-base pair palindromic sequences (5′-TGACGTCA-3′), could not be identified ( Figure 7B ). In addition, the IL-10 enhancer region showed clear differences between the two mouse strains. Within this region, binding sites for Nrf1 were identified, which is a CREB-dependent transcription factor (39). Moreover, we found a change in open chromatin of an alternate promoter of CREM ( Figure 7C ). CREM has been identified as one of the most regulated genes in ST-2 positive colonic T_regs of healthy mice (40). To prove whether CREM is involved in the regulation of ST2, we generated Foxp3^creCREB^fl/flCREM^-/- mice. In vitro differentiation towards Foxp3+ cells was not significantly diminished in Foxp3^creCREB^fl/flCREM^-/- mice ( Figure 7D ). Furthermore, deletion of CREM normalized Foxp3 expression per cell in CREB-deficient T_regs at least to some extent ( Figure 7E ) but reversed the expression of ST2 ( Figure 7F ). Taken together, our data suggest that the interaction of CREB and CREM determines the expression of Foxp3 and ST2 and the induction of CREM in CREB-deficient T_regs contributes to reduced Foxp3 expression. To prove the effect in vivo, we performed a transfer of Foxp3^creCREB^fl/fl CREM^-/- T cells (CD4+CD25-) or appropriate wild-type T cells (CD4+CD25-) into lymphopenic Rag2^-/- mice. The additional genetic deletion of CREM reversed the effect of the CREB deletion and resulted in enhanced colitis severity, measured by JLS (The Jackson Laboratory Scoring) score in the transferred mice ( Figure 7G ).