Significance Th17 cells are a subset of T cells that produce interleukin 17 and other proinflammatory cytokines. They are involved in the development of autoimmune diseases such as multiple sclerosis and rheumatoid arthritis. Previous studies illustrated that RORγt is a driver for Th17 cell differentiation. Here, we reveal REV-ERBα as an antagonist of RORγt. REV-ERBα and RORγt share the same DNA binding motif. REV-ERB can inhibit the expression of RORγt target genes and suppress RORγt-driven Th17 cell differentiation. Treatment with a synthetic REV-ERB agonist delays the onset and impedes the progression of experimental autoimmune encephalomyelitis (EAE), a mouse model of multiple sclerosis. Taken together, our study suggests that modulating REV-ERBα activity may be used to manipulate Th17 cells in autoimmune diseases.

Abstract T helper 17 (Th17) cells produce interleukin-17 (IL-17) cytokines and drive inflammatory responses in autoimmune diseases such as multiple sclerosis. The differentiation of Th17 cells is dependent on the retinoic acid receptor-related orphan nuclear receptor RORγt. Here, we identify REV-ERBα (encoded by Nr1d1), a member of the nuclear hormone receptor family, as a transcriptional repressor that antagonizes RORγt function in Th17 cells. REV-ERBα binds to ROR response elements (RORE) in Th17 cells and inhibits the expression of RORγt-dependent genes including Il17a and Il17f. Furthermore, elevated REV-ERBα expression or treatment with a synthetic REV-ERB agonist significantly delays the onset and impedes the progression of experimental autoimmune encephalomyelitis (EAE). These results suggest that modulating REV-ERBα activity may be used to manipulate Th17 cells in autoimmune diseases.

T helper 17 (Th17) cells are the drivers of inflammatory responses in a large number of autoimmune diseases such as multiple sclerosis, rheumatoid arthritis, and psoriasis (1, 2). The orphan nuclear receptor RORγt is the lineage-specific transcription factor that regulates the differentiation of Th17 cells (3). RORγt expression is induced specifically under Th17 differentiation condition. Once expressed, RORγt in turn binds to the loci of Th17 signature genes Il17a and Il17f and up-regulates their expression (4). Several small-molecule RORγt antagonists were identified that can inhibit Th17 cell differentiation and effector function (5⇓⇓–8). These findings suggested that RORγt inhibitors could be developed for treatment of autoimmune diseases. However, RORγt is also known for its critical role in promoting survival of CD4+CD8+ double-positive (DP) thymocytes. A recent study showed that RORγt inhibitor treatment leads to not only reduced DP thymocyte numbers but also limited T cell repertoire diversity (9). Therefore, it is still a challenge to develop a safe strategy to inhibit RORγt activity in Th17 cells in vivo.

Beyond their critical roles in Th17 cell differentiation, members of the ROR family are known to be key players in the circadian regulatory machinery, where they function as transcriptional activators to turn on the expression of circadian genes (10, 11). In the circadian system, RORs’ transcriptional activity is opposed by a pair of repressors, REV-ERBα and REV-ERBβ. Like RORs, REV-ERBs are also members of the nuclear hormone receptor family and play critical roles in circadian and metabolic regulations (12). REV-ERBs recognize the same RORE DNA sequence as RORs and function as transcriptional repressors to suppress the expression of ROR target genes (13, 14). Although the antagonistic relationship between ROR and REV-ERB was well established in the circadian rhythm system, it is not clear if a similar interaction exists in the T cell lineage.

In this study, we show that REV-ERBα is also a key feedback regulator of RORγt in Th17 cells. REV-ERBα is specifically up-regulated during Th17 differentiation and plays a dual role in Th17 cells. When expressed at a low level, REV-ERBα promotes RORγt expression via the suppression of negative regulator NFIL3 as reported previously (15, 16). At high expression level, REV-ERBα directly competes with RORγt binding to the loci of Th17 signature genes and suppresses Th17 effector function. Elevated REV-ERBα activity also ameliorates Th17-driven autoimmune disease experimental autoimmune encephalomyelitis (EAE). Our results suggest that modulating REV-ERBα activity could provide a way to manipulate Th17 cells in autoimmune diseases.

Discussion In this study, we demonstrated a role for REV-ERBα in the regulation of Th17 cell differentiation and function in addition to its established roles in circadian rhythm and metabolism. REV-ERBα is induced during Th17 cell differentiation and directly competes with RORγt by binding to the RORE sites to repress the expression of key Th17 cell signature genes such as Il17a and Il17f. At the same time, normal RORγt induction is also dependent on repression of Nfil3 by REV-ERBα (15). This is substantiated by reduction of IL-17A production in vitro and milder EAE phenotype in vivo as a result of T cell-specific REV-ERB ablation. These observations suggest that REV-ERBα serves as a feedback regulator for RORγt in T cells, and its expression needs to stay at the right level for optimal Th17 differentiation. A recent study by Amir et al. reported similar results showing reduced Th17 activity when REV-ERB expression is increased (33). However, the same study also showed Th17 differentiation was enhanced in REV-ERBα knockout T cells, which differs from our results and the study performed by Yu et al. (15). One primary difference between the 2 studies is that T cell-specific REV-ERB conditional knockout mice were used in our study, while REV-ERBα germline knockout mice were used in the study by Amir et al. Since REV-ERBα germline knockout mice carried severe defects in circadian and metabolic regulation, it is possible that these perturbations originated outside of the immune system rendered T cells more inflammatory under Th17-inducing conditions. Additionally, differences in gut microbiota between mouse facilities might also contribute to the contradictory results. Given the key role REV-ERBα plays in Th17 cells, we explored if tuning REV-ERBα activity can influence Th17 differentiation and function. Our results showed that elevated REV-ERBα expression in T cells or treatment with REV-ERB ligand SR9009 suppresses Th17 cell differentiation in vitro and inhibits the development of EAE in vivo. Although specific REV-ERBα induction in T cells is sufficient to ameliorate EAE, SR9009 treatment in mice might also impact non-Th17 cells. A previous study demonstrated that REV-ERBα could suppress macrophage expression of IL-6, a key cytokine for Th17 cell differentiation (34). We also observed that subsets of gamma/delta T cells and regulatory T cells could express high levels of REV-ERBα, although the significance of these cell subsets in EAE pathogenesis is currently unclear and requires further characterization. A recent study raised concern on the specificity of SR9009 by demonstrating that SR9009 could exert REV-ERB independent effects in certain tissues, such as mouse embryonic stem cells and hepatocytes (35). In our experiments, SR9009 treatment only affects Th17 differentiation in WT T cells, not REV-ERBα/β double knockout T cells (Fig. 5 D and E), suggesting that SR9009s inhibitory effects on Th17 cells is REV-ERB dependent. A concerted effort has been made to identify RORα/γ antagonists for treatment of Th17-related autoimmune diseases (5⇓⇓–8). In fact, a recent clinical trial on an RORγ antagonist showed encouraging results in psoriasis patients (36). In addition to Th17 cells, RORγt is also highly expressed in developing T cells in the thymus. A recent report showed that RORγ antagonist treatment leads to DP thymocyte apoptosis and reshapes the T cell repertoire by skewing TCRα rearrangement (9). Although limiting the diversity of the T cell repertoire could be beneficial in some autoimmune disease settings, its long-term effect could also increase the risk to cancer and certain infections. In contrast to RORγt, the low expression levels of REV-ERBα and REV-ERBβ in thymocytes and our own results (SI Appendix, Fig. S4) suggest that REV-ERB agonists will not likely have the same impact on thymocytes and the T cell repertoire as RORγ antagonists (37). Therefore, a strategy of targeting REV-ERB alone or in combination with RORγ may provide a unique advantage in developing treatments for Th17 cell-mediated autoimmune diseases.

Materials and Methods Mice. Rosa-M2rtTA, TRE-REV-ERBα, and 2D2 transgenic mice were purchased from Jackson Laboratory. The 3 transgenic lines were crossed to generate Rosa-M2rtTAxTRE-RVBx2D2 triple transgenic mice. REV-ERBαfl/fl/βfl/fl mice were generated previously (14). CD4Cre transgenic, C57BL/6, SJL/J, and Ly5.1+ congenic mice were purchased from the Jackson Laboratory. All mice were maintained in the Salk Institute specific pathogen free (SPF) animal facility in accordance with the protocols approved by the Institutional Animal Care and Use Committee (IACUC) at the Salk Institute. Reverse Transcription and Quantitative PCR. Total RNA was isolated from CD4 T cells using TRIzol reagent (Life Technologies). cDNA was synthesized with iScript Reverse Transcription Supermix for RT-qPCR (Bio-Rad), followed by qPCR using SYBR Green PCR Master Mix (Applied Biosystems). Quantitative PCR was performed on an Applied Biosystems ViiA 7 Real-Time PCR System with gene specific primers listed in SI Appendix, Table S1. Retroviral Transduction. HEK 293T cells were transfected via FuGENE6 reagent (Promega), which contained 0.8 μg of pCL-Eco retroviral packaging plasmid and 1.2 μg of expression plasmid. pCL-Eco was a gift from Inder Verma (Salk Institute, La Jolla, CA) (38). Viral supernatant was harvested 48 and 72 h after transfection. CD4+ T cells were cultured in Th17 polarizing condition and retroviral transduction was performed 24 and 48 h after activation by incubating cells with viral supernatant in the presence of polybrene (4 μg/mL; Millipore) and centrifuged at 2,500 rpm for 90 min at 32 °C. ChIP. Naive CD4+ T cells were activated and polarized in Th17 condition for 3 d for ChIP experiments as described previously (14). Mouse IgG control antibody was purchased from Santa Cruz Biotechnology. RORγt ChIP was performed with a combination of antibodies from BioLegend and Santa Cruz Biotechnologies. REV-ERBα antibody was generated as previously described (14). NCoR1 antibody was purchased from Cell Signaling. Primers spanning the regulatory regions of Il17a, Cry1, and Gmpr are described in SI Appendix, Table S2. ChIP-Seq and Data Analysis. ChIP-seq libraries were constructed and sequenced as described previously (14). Reads were aligned against the mouse mm9 reference genome using the Bowtie2 aligner with standard parameters that allow up to 2 mismatches in the read. Peak calling, motif analyses, and other data analysis were performed using HOMER, a software suite for ChIP-seq analysis as described previously (14). Visualization of ChIP-Seq results was achieved by uploading custom tracks onto the University of California, Santa Cruz (UCSC) genome browser. ChIP-seq data can be accessed in the National Center for Biotechnology Information (NCBI) GEO database under the accession no. GSE72271. RNA-Seq and Data Analysis. RNA-seq libraries were prepared from 100 ng of total RNA (TrueSeq v2, Illumina) and single-ended sequencing was performed on the Illumina HiSeq 2500. Read alignment and junction finding was accomplished using STAR (39) and differential gene expression with Cuffdiff 2 (40). Student’s t test was performed to generate a list of differentially expressed genes (P < 0.05), which was then run through KEGG pathway analysis on DAVID (41, 42) to examine enriched functional groups. Heatmaps were generated on Matrix2png (43). RNA-seq data can be accessed in the NCBI Sequence Read Archive under accession no. SRP062715. EAE Models. For active EAE, mice were immunized s.c. with 200 ng of MOG (35–55) peptide (BL6 mice) or PLP (139–151) peptide (SJL mice) in CFA and received 200 ng of Pertussis toxin intraperitoneally on days 0 and 2. Mice were monitored daily for disease progression. At the end point, the brain and spinal cord were harvested for histology and immune cell profiling. For passive EAE, CD4 T cells from Rosa-M2rtTAxTRE-RVBx2D2 mice were activated under Th17 condition for 3 d, then restimulated overnight in the presence of IL-18 (20 ng/mL; Fisher Scientific). Two to 3 million T cells were adoptively transferred into WT recipient mice, which were given normal water or Doxycycline water to induce REV-ERBα expression. EAE disease progression was monitored as in the active EAE model.

Acknowledgments We thank A. Cheng, Y. Zhang, and C. Gordon for mouse colony management and Y. Dai, M. Ku, S. Heinz, and C. Benner for assistance in RNA-seq experiments. C.C. is supported by the H.A. and Mary K. Chapman Charitable Trust. C.-S.L. is supported by the Albert G. and Olive H. Schlink Foundation. S.P.B. is supported by NIH Grants DK096828 and T32 GM007198. R.M.E. is an Investigator of the Howard Hughes Medical Institute at the Salk Institute and March of Dimes Chair in Molecular and Developmental Biology and is supported by NIH Grants HL088093 and HL105278, Leona M. and Harry B. Helmsley Charitable Trust Grant 2017PG-MED001, Ipsen/Biomeasure, and the Fondation Leducq. Y.Z. is supported by the NOMIS Foundation, the Rita Allen Foundation, National Multiple Sclerosis Society Grant RG4978-A-2, and NIH Grants AI107027 and OD023689. This work was also supported by National Cancer Institute-funded Salk Institute Cancer Center core facilities Grant CA014195. Research reported in this publication was also supported by the National Institute of Environmental Health Sciences of the NIH under Award P42ES010337. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Footnotes Author contributions: C.C., M.D., R.M.E., and Y.Z. designed research; C.C., C.-S.L., X.Z., L.A.S., Y.L., S.P.B., H.C., and T.M.K. performed research; C.C., C.-S.L., L.A.S., M.L., A.R.A., M.D., T.P.B., R.M.E., and Y.Z. analyzed data; and C.C., R.T.Y., M.D., and Y.Z. wrote the paper.

Reviewers: M.O.L., Memorial Sloan Kettering Cancer Center; and D.D.M., Baylor College of Medicine.

The authors declare no conflict of interest.

Data deposition: RNA-Seq data reported in this paper have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database (accession no. PRJNA293472). ChIP-Seq data have been deposited in Gene Expression Omnibus (GEO), www.ncbi.nlm.nih.gov/geo (accession no. GSE72271).

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1907563116/-/DCSupplemental.