Abstract
The transcription factor c-Maf induces the anti-inflammatory cytokine IL-10 in CD4+ T cells in vitro. However, the global effects of c-Maf on diverse immune responses in vivo are unknown. Here we found that c-Maf regulated IL-10 production in CD4+ T cells in disease models involving the TH1 subset of helper T cells (malaria), TH2 cells (allergy) and TH17 cells (autoimmunity) in vivo. Although mice with c-Maf deficiency targeted to T cells showed greater pathology in TH1 and TH2 responses, TH17 cell–mediated pathology was reduced in this context, with an accompanying decrease in TH17 cells and increase in Foxp3+ regulatory T cells. Bivariate genomic footprinting elucidated the c-Maf transcription-factor network, including enhanced activity of NFAT; this led to the identification and validation of c-Maf as a negative regulator of IL-2. The decreased expression of the gene encoding the transcription factor RORγt (Rorc) that resulted from c-Maf deficiency was dependent on IL-2, which explained the in vivo observations. Thus, c-Maf is a positive and negative regulator of the expression of cytokine-encoding genes, with context-specific effects that allow each immune response to occur in a controlled yet effective manner.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Change history
08 February 2019
In the version of this article initially published, the Supplementary Data file was an incorrect version. The correct version is now provided. The error has been corrected in the HTML and PDF version of the article.
References
Sher, A. & Coffman, R. L. Regulation of immunity to parasites by T cells and T cell-derived cytokines. Annu. Rev. Immunol. 10, 385–409 (1992).
Littman, D. R. & Rudensky, A. Y. Th17 and regulatory T cells in mediating and restraining inflammation. Cell 140, 845–858 (2010).
Zhu, J., Yamane, H. & Paul, W. E. Differentiation of effector CD4 T cell populations. Annu. Rev. Immunol. 28, 445–489 (2010).
Gabrysova, L., Howes, A., Saraiva, M. & O’Garra, A. The regulation of IL-10 expression. Curr. Top. Microbiol. Immunol. 380, 157–190 (2014).
Josefowicz, S. Z., Lu, L. F. & Rudensky, A. Y. Regulatory T cells: mechanisms of differentiation and function. Annu. Rev. Immunol. 30, 531–564 (2012).
Apetoh, L. et al. The aryl hydrocarbon receptor interacts with c-Maf to promote the differentiation of type 1 regulatory T cells induced by IL-27. Nat. Immunol. 11, 854–861 (2010).
Ciofani, M. et al. A validated regulatory network for Th17 cell specification. Cell 151, 289–303 (2012).
Cipolletta, D. et al. PPAR-gamma is a major driver of the accumulation and phenotype of adipose tissue Treg cells. Nature 486, 549–553 (2012).
Jones, E. A. & Flavell, R. A. Distal enhancer elements transcribe intergenic RNA in the IL-10 family gene cluster. J. Immunol. 175, 7437–7446 (2005).
Li, P. et al. BATF-JUN is critical for IRF4-mediated transcription in T cells. Nature 490, 543–546 (2012).
Li, W. et al. MiR-568 inhibits the activation and function of CD4+ T cells and Treg cells by targeting NFAT5. Int. Immunol. 26, 269–281 (2014).
Mascanfroni, I. D. et al. Metabolic control of type 1 regulatory T cell differentiation by AHR and HIF1-α. Nat. Med 21, 638–646 (2015).
Motomura, Y. et al. The transcription factor E4BP4 regulates the production of IL-10 and IL-13 in CD4+ T cells. Nat. Immunol. 12, 450–459 (2011).
Neumann, C. et al. Role of Blimp-1 in programing Th effector cells into IL-10 producers. J. Exp. Med. 211, 1807–1819 (2014).
Rutz, S. et al. Notch regulates IL-10 production by T helper 1 cells. Proc. Natl Acad. Sci. USA 105, 3497–3502 (2008).
Rutz, S. et al. Transcription factor c-Maf mediates the TGF-β-dependent suppression of IL-22 production in TH17 cells. Nat. Immunol.1238–1245 (2011)..
Tussiwand, R. et al. Compensatory dendritic cell development mediated by BATF-IRF interactions. Nature 490, 502–507 (2012).
Wan, Y. Y. & Flavell, R. A. Identifying Foxp3-expressing suppressor T cells with a bicistronic reporter. Proc. Natl Acad. Sci. USA 102, 5126–5131 (2005).
Wheaton, J. D., Yeh, C. H. & Ciofani, M. Cutting edge: c-Maf is required for regulatory t cells to adopt RORγt+ and follicular phenotypes. J. Immunol. 199, 3931–3936 (2017).
Xu, M. et al. c-MAF-dependent regulatory T cells mediate immunological tolerance to a gut pathobiont. Nature 554, 373–377 (2018).
Xu, J. et al. c-Maf regulates IL-10 expression during Th17 polarization. J. Immunol. 182, 6226–6236 (2009).
Eychene, A., Rocques, N. & Pouponnot, C. A new MAFia in cancer. Nat. Rev. Cancer 8, 683–693 (2008).
Yoshida, H. & Hunter, C. A. The immunobiology of interleukin-27. Annu. Rev. Immunol. 33, 417–443 (2015).
Barrat, F. J. et al. In vitro generation of interleukin 10-producing regulatory CD4+ T cells is induced by immunosuppressive drugs and inhibited by T helper type 1 (Th1)- and Th2-inducing cytokines. J. Exp. Med. 195, 603–616 (2002).
Wang, Z. Y. et al. Regulation of IL-10 gene expression in Th2 cells by Jun proteins. J. Immunol. 174, 2098–2105 (2005).
Freitas do Rosario, A. P. et al. IL-27 promotes IL-10 production by effector Th1 CD4+ T cells: a critical mechanism for protection from severe immunopathology during malaria infection. J. Immunol. 188, 1178–1190 (2012).
Wilson, M. S. et al. Suppression of allergic airway inflammation by helminth-induced regulatory T cells. J. Exp. Med. 202, 1199–1212 (2005).
Korn, T. et al. IL-6 controls Th17 immunity in vivo by inhibiting the conversion of conventional T cells into Foxp3+ regulatory T cells. Proc. Natl Acad. Sci. USA 105, 18460–18465 (2008).
Coomes, S.M. et al. CD4 Th2 cells are directly regulated by IL-10 during allergic airway inflammation. Mucosal Immunol. 10, 150–161 (2016).
Bettelli, E. et al. IL-10 is critical in the regulation of autoimmune encephalomyelitis as demonstrated by studies of IL-10- and IL-4-deficient and transgenic mice. J. Immunol. 161, 3299–3306 (1998).
Honma, S. et al. Dec1 and Dec2 are regulators of the mammalian molecular clock. Nature 419, 841–844 (2002).
Ho, I. C., Hodge, M. R., Rooney, J. W. & Glimcher, L. H. The proto-oncogene c-maf is responsible for tissue-specific expression of interleukin-4. Cell 85, 973–983 (1996).
Ho, I. C., Lo, D. & Glimcher, L. H. c-maf promotes T helper cell type 2 (Th2) and attenuates Th1 differentiation by both interleukin 4-dependent and -independent mechanisms. J. Exp. Med. 188, 1859–1866 (1998).
Andris, F. et al. The transcription factor c-Maf promotes the differentiation of follicular helper T cells. Front. Immunol. 8, 480 (2017).
Bauquet, A. T. et al. The costimulatory molecule ICOS regulates the expression of c-Maf and IL-21 in the development of follicular T helper cells and TH-17 cells. Nat. Immunol. 10, 167–175 (2009).
Perez-Mazliah, D. et al. Follicular helper T cells are essential for the elimination of plasmodium infection. EBioMedicine 24, 216–230 (2017).
Ma, W., Noble, W. S. & Bailey, T. L. Motif-based analysis of large nucleotide data sets using MEME-ChIP. Nat. Protoc. 9, 1428–1450 (2014).
Chuang, L. S., Ito, K. & Ito, Y. RUNX family: regulation and diversification of roles through interacting proteins. Int. J. Cancer 132, 1260–1271 (2013).
Wang, S. et al. Target analysis by integration of transcriptome and ChIP-seq data with BETA. Nat. Protoc. 8, 2502–2515 (2013).
BaekS., GoldsteinI. & HagerG. L. Bivariate genomic footprinting detects changes in transcription factor activity. Cell Rep. 19, 1710–1722 (2017).
Djuretic, I. M. et al. Transcription factors T-bet and Runx3 cooperate to activate Ifng and silence Il4 in T helper type 1 cells. Nat. Immunol. 8, 145–153 (2007).
Kataoka, K., Noda, M. & Nishizawa, M. Maf nuclear oncoprotein recognizes sequences related to an AP-1 site and forms heterodimers with both Fos and Jun. Mol. Cell. Biol. 14, 700–712 (1994).
Lin, C. C. et al. Bhlhe40 controls cytokine production by T cells and is essential for pathogenicity in autoimmune neuroinflammation. Nat. Commun. 5, 3551 (2014).
Muller, M. R. & Rao, A. NFAT, immunity and cancer: a transcription factor comes of age. Nat. Rev. Immunol. 10, 645–656 (2010).
Webster, K. E. et al. In vivo expansion of T reg cells with IL-2-mAb complexes: induction of resistance to EAE and long-term acceptance of islet allografts without immunosuppression. J. Exp. Med. 206, 751–760 (2009).
Laurence, A. et al. Interleukin-2 signaling via STAT5 constrains T helper 17 cell generation. Immunity 26, 371–381 (2007).
Kamanaka, M. et al. Expression of interleukin-10 in intestinal lymphocytes detected by an interleukin-10 reporter knockin tiger mouse. Immunity 25, 941–952 (2006).
Wende, H. et al. The transcription factor c-Maf controls touch receptor development and function. Science 335, 1373–1376 (2012).
Lee, P. P. et al. A critical role for Dnmt1 and DNA methylation in T cell development, function, and survival. Immunity 15, 763–774 (2001).
Kaji, T. et al. Distinct cellular pathways select germline-encoded and somatically mutated antibodies into immunological memory. J. Exp. Med. 209, 2079–2097 (2012).
Freitas do Rosario, A. P. et al. Gradual decline in malaria-specific memory T cell responses leads to failure to maintain long-term protective immunity to Plasmodium chabaudi AS despite persistence of B cell memory and circulating antibody. J. Immunol. 181, 8344–8355 (2008).
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).
Acknowledgements
We thank R.A. Flavell (Yale University) for Foxp3RFP IL-10GFP mice; M. Sieweke and C. Birchmeier (Max Delbrück Centre for Molecular Medicine) for Maffl/fl mice; G. Trinchieri (Wistar Institute) for anti-IL-12p40 (C17.8.20); The Francis Crick Institute, Biological Services for breeding and maintenance of the mice; the Advanced Sequencing Platform and A. Sesay for help with sequence sample processing; the Flow Cytometry Platform; Bioinformatics Platform and G. Kelly for help with statistics; Photographics and M. Butt for help with figures; V. Stavropoulos for help with in vivo experiments; and A. Singhania and L. Moreira-Teixeira from the AOG laboratory for review and discussion of the manuscript. Supported by the Francis Crick Institute (Crick Core), which since 1 April 2015 has received its core funding from Cancer Research UK (FC001126 and FC010110), the UK Medical Research Council (FC001126 and FC010110) and the Wellcome Trust (FC001126 and FC010110), and before that from the UK Medical Research Council (MRC U117565642) and the European Research Council (294682-TB-PATH (Crick 10127)) (all for A.O.G., L.G., K.P., M.A.-M., L.S.C. and C.W.), the UK Medical Research Council (MRC Centenary Award for L.G.; and MRC eMedLab Medical Bioinformatics Infrastructure Award MR/L016311/1 for N.M.L.), Crick Core projects (10101 for J.L. and FC001051 for J.B. and V.M.), the Wellcome Trust (WT098326MA for J.B. and V.M.; and Joint Investigator Award 103760/Z/14/Z for N.M.L.), Inserm/CNRS and Agence Nationale de la Recherche (ANR-11-BSV3-0026), Fondation pour la Recherche Médicale (DEQ. 20110421320) and the European Research Council (695093 for M.H.S.).
Author information
Authors and Affiliations
Contributions
L.G. co-designed the study with A.O.G., executed the experiments, interpreted and analyzed the data, and co-wrote the paper with A.O.G.; M.A.-M. analyzed the ATAC-seq, ChIP-seq and RNA-seq data and contributed to the writing of the paper; R.L. interpreted and analyzed the RNA-seq data and contributed to the writing of the paper; L.S.C. executed and helped design the in vitro experiments with c-Maf-deficient and control CD4+ T cells and analyzed the data; J.S. and C.H. helped execute and interpret malaria experiments; D.P.-M. contributed data for Supplementary Fig. 3; C.W. helped execute EAE experiments; Y.K. and M.W. helped execute and interpret allergy experiments; K.P. performed early RNA-seq analysis; X.W. executed the genetics for obtaining Cd4-cre × Maffl/fl mice and designed and performed all screening and quality control; L.B. performed processing and troubleshooting for RNA-seq analysis; H.W. constructed Maffl/fl mice and provided feedback on the study; M.H.S. provided feedback and suggestions for the study; G.E. supervised analysis of early RNA-seq data; J.B. and V.M. provided advice and input on the ATAC-seq analysis; J.L. provided expertise for the malaria model and feedback on the study; N.M.L. provided advice and input on the RNA-seq analysis and directed the integrated analysis of ATAC-seq, ChIP-seq and RNA-seq; and A.O.G. co-designed the study with L.G., interpreted and analyzed the data, and co-wrote the paper with L.G.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Integrated supplementary information
Supplementary Figure 1 The induction and effect of c-Maf on CD4+ T cell differentiation in vitro
a, Naive CD4+ T cells from Maf fl/fl and Maf fl/flCd4-cre were sorted and stimulated in vitro with anti-CD3 and anti-CD28 in the presence of medium alone, IL-12, IL-27, IL-12 + IL-27, IL-4, TGF-β + IL-6 or TGF-β and assessed for the mRNA expression of Maf, Il10 and master regulator transcription factors Tbx21, Gata3, Rorc and Foxp3 and hallmark cytokines Ifng, Il4 and Il17a as well as Il2ra relative to Hprt as follows. Medium, IL-12, IL-27, IL-12 + IL-27: Maf, Il10, Tbx21, Ifng (day 3); IL-4: Maf (day 5), Il10 (day 5), Gata3 (day 4), Il4 (day 5); TGF-β + IL-6: Maf (day 1), Il10 (day 2), Il17a (day 5); TGF-β: Maf, Il10, Foxp3, Il2ra (day 3) (n = 3 culture wells per condition, mean ± SD; * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001, unpaired t-test, two-tailed). Representative data from three biological experiments are shown. b, Naive CD4+ T cells from wild-type mice were sorted, stimulated as in (a) and assessed for intracellular c-Maf on day 3. Depicted are dot plots of c-Maf versus isotype control gated on live CD4+ T cells. Representative data from two independent experiments are shown.
Supplementary Figure 2 Supporting information for differential gene expression analyses
CD4+ T cells from malaria, HDM and EAE challenged Maffl/flCd4-cre vs Maffl/fl mice were profiled by RNA-seq. a, Volcano plots of differentially expressed genes, with previously associated regulators of IL-10 depicted (blue, significantly down-regulated; red, significantly up-regulated; grey, non-differentially expressed) (n = 3 independent animals (malaria) or biologically independent samples (HDM and EAE) per genotype; P < 0.05, absolute FC ≥ 1.5, moderated t-test, two-tailed). b, Manually curated list of top biological pathways as determined by GO enrichment analysis of each differentially up- and down-regulated genes in Maffl/flCd4-cre vs Maffl/fl mice (n = 3 independent animals (malaria) or biologically independent samples (HDM and EAE) per genotype).
Supplementary Figure 3 Effect on pathology and phenotype of TFH cells in acute phase of malaria
a, Schematic of P. chabaudi infection in Bcl6fl/fl and Bcl6fl/flCd4-cre mice, percentage weight loss (n = 5, mean ± SD) and temperature changes (n = 8, mean ± SD) on day 9 post P. chabaudi infection. Representative data from two biological experiments are shown. b, Representative cytokine staining of CD4+ T cells on day 14 post P. chabaudi infection in C57BL/6/J mice, plots are gated on live CD3+CD4+CD44+ T cells. Pooled data from two biological experiments are shown (n = 5, mean ± SD).
Supplementary Figure 4 Changes in chromatin accessibility do not account for transriptional disregulation in the absence of c-Maf
Volcano plots of accessibility changes in ATAC-Seq consensus peak sets in CD4+ T cells from malaria, HDM allergy and EAE challenged Maffl/flCd4-cre vs Maffl/fl mice (n = 3 independent animals (malaria) or biologically independent samples (HDM and EAE) per genotype, statistical significance called using DiffBind 2.02 with FDR < 0.05, absolute fold change ≥ 1.5) assigned to genes (see Supplementary Information for computational methods) and mapped to RNA-seq fold-change values. The top ten peaks ranked by fold-change were labeled with their assigned gene, as well as any remodeled peak assigned to Il10.
Supplementary Figure 5 Framework schematic for the identification of putative direct targets of c-Maf
For each disease model, the c-Maf ChIP-seq (GSE40918) and motif datasets were filtered according to the accessibility as determined by ATAC-seq, allowing the identification of putative c-Maf binding sites and estimation of its relevance in explaining RNA-seq-defined transcriptional changes observed upon c-Maf deletion (see Supplementary Information for computational methods).
Supplementary Figure 6 Genome browser tracks of other key immune genes
Genome browser tracks of read coverage of RNA-seq and ATAC-seq in CD4+ T cells from the malaria, HDM allergy and EAE challenged Maffl/flCd4-cre vs Maffl/fl mice (shown as an overlay of n = 3 independent animals (malaria) or biologically independent samples (HDM and EAE) per genotype), as compared to untreated control and matched to c-Maf ChIP-seq (GSE40918) and motif sites.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1-6
Supplementary Table 1
TF correlation lists
Supplementary Table 2
SVD components
Supplementary Table 3
Differentially expressed genes
Supplementary Table 4
Network analysis
Supplementary Table 5
Direct and indirect c-Maf targets
Supplementary Table 6
Combined c-Maf binding evidence for direct effects on differentially expressed genes
Supplementary Table 7
BaGFoot TF statistics
Supplementary Table 8
BaGFoot TFs with altered activity are statistically enriched in differentially expressed genes
Supplementary Data
Supplementary Data for Computational Methods
Rights and permissions
About this article
Cite this article
Gabryšová, L., Alvarez-Martinez, M., Luisier, R. et al. c-Maf controls immune responses by regulating disease-specific gene networks and repressing IL-2 in CD4+ T cells. Nat Immunol 19, 497–507 (2018). https://doi.org/10.1038/s41590-018-0083-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41590-018-0083-5
This article is cited by
-
Blimp-1 and c-Maf regulate immune gene networks to protect against distinct pathways of pathobiont-induced colitis
Nature Immunology (2024)
-
Semaphorin 3 a restores the ability of type 1 regulatory T cells to suppress food allergy
Immunologic Research (2024)
-
The neuroimmune axis of Alzheimer’s disease
Genome Medicine (2023)
-
Microbiota-assisted iron uptake promotes immune tolerance in the intestine
Nature Communications (2023)
-
Single cell transcriptomics shows that malaria promotes unique regulatory responses across multiple immune cell subsets
Nature Communications (2023)