Varieties of RNA modification form the epitranscriptome for post-transcriptional regulation1. 5-Methylcytosine (5-mC) is a sparse RNA modification in messenger RNA (mRNA) under physiological conditions2. The function of RNA 5-hydroxymethylcytosine (5-hmC) oxidized by ten-eleven translocation (Tet) proteins in Drosophila has been revealed more recently3,4. However, the turnover and function of 5-mC in mammalian mRNA have been largely unknown. Tet2 suppresses myeloid malignancies mostly in an enzymatic activity-dependent manner5, and is important in resolving inflammatory response in an enzymatic activity-independent way6. Myelopoiesis is a common host immune response in acute and chronic infections; however, its epigenetic mechanism needs to be identified. Here we demonstrate that Tet2 promotes infection-induced myelopoiesis in an mRNA oxidation-dependent manner through Adar1-mediated repression of Socs3 expression at the post-transcription level. Tet2 promotes both abdominal sepsis-induced emergency myelopoiesis and parasite-induced mast cell expansion through decreasing mRNA levels of Socs3, a key negative regulator of the JAK–STAT pathway that is critical for cytokine-induced myelopoiesis. Tet2 represses Socs3 expression through Adar1, which binds and destabilizes Socs3 mRNA in a RNA editing-independent manner. For the underlying mechanism of Tet2 regulation at the mRNA level, Tet2 mediates oxidation of 5-mC in mRNA. Tet2 deficiency leads to the transcriptome-wide appearance of methylated cytosines, including ones in the 3′ untranslated region of Socs3, which influences double-stranded RNA formation for Adar1 binding, probably through cytosine methylation-specific readers, such as RNA helicases. Our study reveals a previously unknown regulatory role of Tet2 at the epitranscriptomic level, promoting myelopoiesis during infection in the mammalian system by decreasing 5-mCs in mRNAs. Moreover, the inhibitory function of cytosine methylation on double-stranded RNA formation and Adar1 binding in mRNA reveals its new physiological role in the mammalian system.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Signal Transduction and Targeted Therapy Open Access 27 October 2023
Signal Transduction and Targeted Therapy Open Access 11 August 2023
Cell Discovery Open Access 08 August 2023
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 51 print issues and online access
$199.00 per year
only $3.90 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
Fu, Y., Dominissini, D., Rechavi, G. & He, C. Gene expression regulation mediated through reversible m6A RNA methylation. Nat. Rev. Genet. 15, 293–306 (2014)
Zhao, B. S., Roundtree, I. A. & He, C. Post-transcriptional gene regulation by mRNA modifications. Nat. Rev. Mol. Cell Biol. 18, 31–42 (2017)
Delatte, B. et al. Transcriptome-wide distribution and function of RNA hydroxymethylcytosine. Science 351, 282–285 (2016)
Fu, L. et al. Tet-mediated formation of 5-hydroxymethylcytosine in RNA. J. Am. Chem. Soc. 136, 11582–11585 (2014)
Álvarez-Errico, D., Vento-Tormo, R., Sieweke, M. & Ballestar, E. Epigenetic control of myeloid cell differentiation, identity and function. Nat. Rev. Immunol. 15, 7–17 (2015)
Zhang, Q. et al. Tet2 is required to resolve inflammation by recruiting Hdac2 to specifically repress IL-6. Nature 525, 389–393 (2015)
Moran-Crusio, K. et al. Tet2 loss leads to increased hematopoietic stem cell self-renewal and myeloid transformation. Cancer Cell 20, 11–24 (2011)
Weber, G. F. et al. Interleukin-3 amplifies acute inflammation and is a potential therapeutic target in sepsis. Science 347, 1260–1265 (2015)
Lantz, C. S. et al. Role for interleukin-3 in mast-cell and basophil development and in immunity to parasites. Nature 392, 90–93 (1998)
He, C. et al. High-resolution mapping of RNA-binding regions in the nuclear proteome of embryonic stem cells. Mol. Cell 64, 416–430 (2016)
Van Nostrand, E. L. et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nat. Methods 13, 508–514 (2016)
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010)
Nishikura, K. A-to-I editing of coding and non-coding RNAs by ADARs. Nat. Rev. Mol. Cell Biol. 17, 83–96 (2016)
Anantharaman, A. et al. ADAR2 regulates RNA stability by modifying access of decay-promoting RNA-binding proteins. Nucleic Acids Res. 45, 4189–4201 (2017)
Sakurai, M. et al. ADAR1 controls apoptosis of stressed cells by inhibiting Staufen1-mediated mRNA decay. Nat. Struct. Mol. Biol. 24, 534–543 (2017)
Grzechnik, P., Gdula, M. R. & Proudfoot, N. J. Pcf11 orchestrates transcription termination pathways in yeast. Genes Dev. 29, 849–861 (2015)
Behm-Ansmant, I., Gatfield, D., Rehwinkel, J., Hilgers, V. & Izaurralde, E. A conserved role for cytoplasmic poly(A)-binding protein 1 (PABPC1) in nonsense-mediated mRNA decay. EMBO J. 26, 1591–1601 (2007)
Hu, L. et al. Crystal structure of TET2–DNA complex: insight into TET-mediated 5mC oxidation. Cell 155, 1545–1555 (2013)
Kohli, R. M. & Zhang, Y. TET enzymes, TDG and the dynamics of DNA demethylation. Nature 502, 472–479 (2013)
Goll, M. G. et al. Methylation of tRNAAsp by the DNA methyltransferase homolog Dnmt2. Science 311, 395–398 (2006)
Jarmoskaite, I. & Russell, R. RNA helicase proteins as chaperones and remodelers. Annu. Rev. Biochem. 83, 697–725 (2014)
Popis, M. C., Blanco, S. & Frye, M. Posttranscriptional methylation of transfer and ribosomal RNA in stress response pathways, cell differentiation, and cancer. Curr. Opin. Oncol. 28, 65–71 (2016)
Amort, T. et al. Long non-coding RNAs as targets for cytosine methylation. RNA Biol. 10, 1003–1008 (2013)
Hussain, S. et al. NSun2-mediated cytosine-5 methylation of vault noncoding RNA determines its processing into regulatory small RNAs. Cell Reports 4, 255–261 (2013)
Aas, P. A. et al. Human and bacterial oxidative demethylases repair alkylation damage in both RNA and DNA. Nature 421, 859–863 (2003)
Edelheit, S., Schwartz, S., Mumbach, M. R., Wurtzel, O. & Sorek, R. Transcriptome-wide mapping of 5-methylcytidine RNA modifications in bacteria, archaea, and yeast reveals m5C within archaeal mRNAs. PLoS Genet. 9, e1003602 (2013)
Luo, Y., Feng, J., Xu, Q., Wang, W. & Wang, X. NSun2 deficiency protects endothelium from inflammation via mRNA methylation of ICAM-1. Circ. Res. 118, 944–956 (2016)
Rittirsch, D., Huber-Lang, M. S., Flierl, M. A. & Ward, P. A. Immunodesign of experimental sepsis by cecal ligation and puncture. Nat. Protocols 4, 31–36 (2009)
Yu, M. et al. Tet-assisted bisulfite sequencing of 5-hydroxymethylcytosine. Nat. Protocols 7, 2159–2170 (2012)
Li, X. et al. Transcriptome-wide mapping reveals reversible and dynamic N1-methyladenosine methylome. Nat. Chem. Biol. 12, 311–316 (2016)
Liddicoat, B. J. et al. RNA editing by ADAR1 prevents MDA5 sensing of endogenous dsRNA as nonself. Science 349, 1115–1120 (2015)
Austin, E. G. et al. Improvements to the HITS-CLIP protocol eliminate widespread mispriming artifacts. BMC Genomics 17, 338 (2016)
Zhang, C. & Darnell, R. B. Mapping in vivo protein–RNA interactions at single-nucleotide resolution from HITS-CLIP data. Nat. Biotechnol. 29, 607–614 (2011)
Keene, J. D., Komisarow, J. M. & Friedersdorf, M. B. RIP-Chip: the isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts. Nat. Protocols 1, 302–307 (2006)
Dominissini, D., Moshitch-Moshkovitz, S., Salmon-Divon, M., Amariglio, N. & Rechavi, G. Transcriptome-wide mapping of N6-methyladenosine by m6A-seq based on immunocapturing and massively parallel sequencing. Nat. Protocols 8, 176–189 (2013)
Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protocols 7, 562–578 (2012)
Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015)
Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010)
Ramaswami, G. et al. Identifying RNA editing sites using RNA sequencing data alone. Nat. Methods 10, 128–132 (2013)
Peng, Z. et al. Comprehensive analysis of RNA-seq data reveals extensive RNA editing in a human transcriptome. Nat. Biotechnol. 30, 253–260 (2012)
Liang, F. et al. BS-RNA: an efficient mapping and annotation tool for RNA bisulfite sequencing data. Comput. Biol. Chem. 65, 173–177 (2016)
We thank R. L. Levine for providing Tet2 knockout mice, and K. Wang and C. Yi for helping with LC–MS analysis of RNA methylation. We thank C. Hu and W. Huang for technician support. This work was supported by grants from the National Natural Science Foundation of China (81788101, 31390431, 91542204, 31670884), the Shanghai Rising-Star Program (17QA1405300) and the CAMS Innovation Fund for Medical Science (2016-12M-1-003).
The authors declare no competing financial interests.
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, In vivo experimental design of transplantation and infection studies with bone marrow cells from Tet2-deficient (knockout) and littermate control (wild-type) mice. b, Quantitative assessment of toluidine blue-positive mast cells in the intestinal tissues (n = 6 biologically independent mice). c, Representative photomicrographs of toluidine blue-stained tissue sections derived from KitW-sh/W-sh mice transplanted with bone marrow cells from the indicated genotypes. Arrows indicate mast cells. Scale bars, 50 μm. *P < 0.05, **P < 0.01, unpaired two-sided Student’s t-test. Mean and s.d. of n samples (b). Data are representative of three independent experiments with similar results (c).
a–c, qPCR analysis of mRNA levels of indicated genes in wild-type (WT) and Tet2-deficient (KO) BMMCs treated with IL-3 (10 ng ml−1). d, e, Immunoblot assays of the phosphorylated (p-) or total proteins in lysates of wild-type and knockout BMMCs (d) and bone marrow cells (e) stimulated with IL-3 for the indicated time. Bone marrow cells were collected from Tet2-deficient (knockout) and littermate control (wild-type) mice and pre-stimulated with IL-3 for 12 h. f, Immunoblot assays of the phosphorylated (p-) or total proteins in lysates of knockout BMMCs treated with non-targeting control siRNA (siCtrl) or Socs3-specific siRNA (siSocs3). Before being re-stimulated for the indicated times for subsequent analysis, BMMCs and bone marrow cells were starved for 12 h in the absence of cytokines. *P < 0.05, **P < 0.01, unpaired two-sided Student’s t-test. Mean and s.e.m. of triplicate biological replicates (a–c). Blots are representative of three independent experiments (d–f).
a, b, Bisulfite-PCR assay of methylation states of CG dinucleotides in DNA regions of chromosome 11: 117969004-258 (a) or chromosome 11: 117969363-777 (b) in Tet2-deficient BMMCs and the control cells. c, Wild-type and knockout BMMCs were starved for 12 h in the absence of cytokines, and then treated with 5 mg ml−1 actinomycin D (actD) for 0, 15, 30, 60 min. Socs3 mRNA decay was quantified by qPCR and normalization by β-actin. d, Immunoblot of Tet2 immunoprecipitation during CLIP. Black line indicates region excised for CLIP library preparation. e, PCR amplification products from CLIP experiments before indexing. Red box indicates gel region where DNA products were extracted for further indexing and high-throughput sequencing. Biorep 1, 2 and 3 are biological replicates from three BMMC samples which have different culture start dates and crosslinked end dates. f, Pairwise correlation analysis between biological replicates with normalized tag numbers in common peaks (from left to right: biorep 1 versus biorep 2, biorep 1 versus biorep 3, biorep 2 versus biorep 3). *P < 0.05, **P < 0.01, unpaired two-sided Student’s t-test. Mean and s.d. of triplicate biological replicates (c). Blots are representative of three independent experiments (d).
a, b, ViennaRNA prediction of secondary structure of sequences near editing sites in Socs3 and Lrrc47 3′ UTR. Arrows highlight edited adenosines. c, Experimental validation of the A-to-G mutation (0) and the nearby adenosines (−2, −1, 1, 2) in control BMMCs. d, RIP–qPCR analysis of Socs3 or Lrrc47 transcripts in RNAs from anti-Adar1 immunoprecipitated wild-type and knockout BMMCs lysates. e, Immunoblot of ADAR1 immunoprecipitation during CLIP. Black line indicates region excised for CLIP RNA preparation. f, RT–PCR sequencing assay of A-to-G mutation frequencies in Socs3 mRNA from wild-type BMMCs at the indicated culture stages. g, Immunoblot of Adar1 protein expression in BMMCs from wild-type and Tet2-deficient (knockout) mice. h, Immunoblot of Adar1 among cytoplasm and nuclear proteins of BMMCs. i, Immunoblot of Adar1 protein expression in BMMCs treated with non-targeting control siRNA (siCtrl) or Adar1-specific siRNA (siAdar1). j, qPCR analysis of HEK293T cells transiently transfected for 24 h with vectors coding haemagglutinin-tagged Socs3, Flag-tagged Adar1 and indicated Myc-tagged Tet2 mutants. k, Dot blot assays of 5-hmC levels in 10 ng DNA from Tet2- and Tet2 mutant-overexpressed HEK293T cells. Error bars, s.d. of triplicate technical replicates (d, j). Blots are representative of three independent experiments (e, g–i, k).
a, One microgram of in vitro transcribed RNAs containing 1% 5-mC, or 3% mixture of 5-hmC, 5-fC and 5-caC was analysed by dot blots using 5-mC antibody. b, c, The 5-mC levels in mRNAs (b) and 5-hmC and 5-caC levels of DNAs (c) from in vitro Tet2 oxidation assay with or without α-KG were analysed by dot blots. Twofold gradient dilutions of 20 ng synthetic Socs3 mRNAs (b) and 10 ng DNAs (c) after oxidation were used for quantification. d, LC–MS for quantifying 5-mC levels of mRNAs from HEK293T cells overexpressing the indicated mutant forms of Tet2. e, g, Dot blot assays of 5-mC levels in 800 ng mRNAs (e) and 1 μg total RNA (g) from Tet2- and Tet2∆DNA mutant-overexpressed HEK293T cells. Twofold gradient dilutions of 800 ng in vitro transcribed Socs3 mRNAs containing 0.4% 5-mCs were used for the dilution curve of grey value-based quantification. f, In vitro RNA 5-mC oxidation assay of Tet2 mutants. The overexpressed Myc-tagged Tet2 mutants immunoprecipited from HEK293T cells were subjected to in vitro oxidation. Oxidized RNAs pretreated with DNase were used for dot blot analysis of 5-hmC levels. h, Bisulfite-PCR assay of the 4th to 14th cytosines in tRNAAsp(GUC) in Tet2-overexpressed HEK293T cells or Tet2-deficient BMMCs and the control cells. i, j, Immunoblot of Tet2 protein expression and LC–MS for quantifying 5-mC levels of mRNAs in HEK293T cells treated with non-targeting control siRNA (siCtrl) or Tet2-specific siRNA (siTet2). Mean and s.d of triplicate technical replicates (b, d, e, g, j). Blots are representative of three independent experiments (a–c, e–g, i).
a, Overlap rates of methylcytosines with methylation levels above the indicated values in bisulfite sequencing assay between indicated technical replicates for Tet2-deficient (knockout, K1/2) and control (wild-type, W1/2) groups. b, Overlap rates of methylcytosines between the two biological replicates from common cytosines with read coverage above four. c, Methylcytosines in the knockout group were chosen, and mean methylation rates of these methylcytosine sites in both the wild-type and knockout groups were categorized with indicated variation folds and are presented in the scatter plot. Different colours indicate the variation of mean methylation levels of each of the methylcytosines in the knockout group compared with those in the wild-type group. d, Fraction of genes associated with knockout group-specific methylcytosines (mCgene) or CLIP peaks (CLIPgene) with variations of mRNA levels (>1.3-fold, up; <0.77-fold, down; P < 0.05) in the knockout group, compared with the control group. e, Exon-located CLIP peak and methylcytosine in the same gene were chosen, and the distance in mature mRNA between the CLIP peak boundary and the methylcytosine clusters with the shortest gap was calculated. These distances for each of the genes are presented in the box plot (centre, median; box boundaries, 25% and 75% percentiles; whiskers, 1.5-fold interquartile range; diamond, outlier; n = 11 distance values). f, Bisulfite-PCR sequencing assay of cytosine sites with methylation-supported reads in the 3′ UTR of Socs3. g, Genome browser views of gene loci containing 5-mCs in the Tet2-deficient group. Black signals indicate mean mC-supporting read numbers of all the replicates in the Tet2-deficient group. h, Genome browser view of the indicated region with RepeatMasker Viz containing the editing site in the 3′ UTR of Zfp65. i, ViennaRNA prediction of secondary structure of sequences containing the methylation sites in the 3′ UTR of Tmed10. j, qPCR analysis of gene transcripts from anti-5-mC immuno-selected RNAs from total RNAs of wild-type and knockout BMMCs. Unmethylated and methylated spike-ins as the negative and positive controls. Cytosine with coverage above 4, at least two reads supporting methylation and methylation level equal or above 0.1 was chosen as methylcytosine, considering both boinformatic and biological significance. Mean and s.d of triplicate technical replicates (j).
a, qPCR analysis of overexpressed Socs3 transcripts from anti-5-mC immuno-selected RNAs from total RNAs of HEK293T cells transfected with Tet2 or Tet2 mutants. b, qPCR analysis of Socs3 transcripts from specific-modification antibodies immuno-selected RNAs from total RNAs of wild-type BMMCs. Unmodified and modified spike-ins as the negative and positive controls. c, qPCR analysis of HEK293T cells transiently transfected for 24 h with vectors coding haemagglutinin-tagged wild-type Socs3 or C-to-G mutant Socs3 (Socs3C-to-G), with or without Flag-tagged Adar1 and Myc-tagged Tet2. d, RIP–qPCR analysis of Socs3 3′ UTR levels in RNAs from Flag-tagged Adar1-immunoprecipitated HEK293T cell lysates overexpressed with Socs3 or Socs3C-to-G together with Adar1. Lysates (1%) were used for normalization as input. e, A-to-I editing rates in Socs3 3′ UTR with cytosine or 5-mC after Adar1 editing in vitro. f, Socs3 transcript levels determined by RT-qPCR from J2 immuno-selected dsRNA; p1, primer 1; p2, primer 2. Mean and s.d. of triplicate technical replicates (a–d, f). Data are representative of three independent experiments (e).
a, Genome browser view of sequencing data on Socs3 locus. Blue, A-to-G mutant reads in wild-type BMMCs; red, mean mC-supporting read numbers in knockout BMMCs; black, CLIP tag coverage. b, Tet2 promotes mRNA cytosine demethylation for effective formation of dsRNA which is bound by Adar1, leading to the suppression of Socs3 expression at the post-transcriptional level.
About this article
Cite this article
Shen, Q., Zhang, Q., Shi, Y. et al. Tet2 promotes pathogen infection-induced myelopoiesis through mRNA oxidation. Nature 554, 123–127 (2018). https://doi.org/10.1038/nature25434
This article is cited by
Aberrant m5C hypermethylation mediates intrinsic resistance to gefitinib through NSUN2/YBX1/QSOX1 axis in EGFR-mutant non-small-cell lung cancer
Molecular Cancer (2023)
NSUN2 promotes osteosarcoma progression by enhancing the stability of FABP5 mRNA via m5C methylation
Cell Death & Disease (2023)
Cell Discovery (2023)
Cell Research (2023)
Nature Reviews Immunology (2023)