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Metabolic control of DNA methylation in naive pluripotent cells

Abstract

Naive epiblast and embryonic stem cells (ESCs) give rise to all cells of adults. Such developmental plasticity is associated with genome hypomethylation. Here, we show that LIF–Stat3 signaling induces genomic hypomethylation via metabolic reconfiguration. Stat3−/− ESCs show decreased α-ketoglutarate production from glutamine, leading to increased Dnmt3a and Dnmt3b expression and DNA methylation. Notably, genome methylation is dynamically controlled through modulation of α-ketoglutarate availability or Stat3 activation in mitochondria. Alpha-ketoglutarate links metabolism to the epigenome by reducing the expression of Otx2 and its targets Dnmt3a and Dnmt3b. Genetic inactivation of Otx2 or Dnmt3a and Dnmt3b results in genomic hypomethylation even in the absence of active LIF–Stat3. Stat3−/− ESCs show increased methylation at imprinting control regions and altered expression of cognate transcripts. Single-cell analyses of Stat3−/− embryos confirmed the dysregulated expression of Otx2, Dnmt3a and Dnmt3b as well as imprinted genes. Several cancers display Stat3 overactivation and abnormal DNA methylation; therefore, the molecular module that we describe might be exploited under pathological conditions.

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Fig. 1: LIF–Stat3 induces hypomethylation in ESCs via Dnmt3a/b regulation.
Fig. 2: Impact of Stat3 on DNA methylation and transcription.
Fig. 3: Nuclear Stat3 does not regulate Dnmt3a/b and 5mC.
Fig. 4: Stat3 controls DNA methylation via metabolic regulation.
Fig. 5: Alpha-ketoglutarate regulates 5mC mainly by controlling the levels of Dnmt3a/b.
Fig. 6: Otx2 links αKG to Dnmt3a/b expression.
Fig. 7: Mitochondrial Stat3 regulates ESC differentiation.
Fig. 8: Stat3 regulates Dnmts and imprinted transcripts in early mouse blastocysts.

Data availability

Bulk and single-cell RNA-seq and RRBS data generated during the current study are available at the Gene Expression Omnibus (GEO) repository under the accession numbers GSE133926 and GSE134450. All RNA-seq and RRBS process data used in Figs. 1d,i, 2a–e,h, 4c, 5d, 6b,d, 7a–e, 8a–g and Extended Data Figs. 1a,b,e, 2b–k, 3b,c, 5c, 7a–d, 8a–f are reported in Supplementary Tables 1, 2 and 4. The RNA-seq data of Rex1-GFPd2 cells can be found at GEO under the accession number GSE111694. Mass spectrometry proteomic data of the following samples: S3+/+ cells in 2i; S3+/+, S3−/−, MitoS3.A and MitoS3.B cells in 2iLIF used in Figs. 1f, 5g, and Extended Data Fig. 1c are reported in Supplementary Table 3 and on ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD020385. The primers and oligonucleotide sequences are in Supplementary Tables 68. Additional data that support the findings of this study, such as mass spectrometry measurements, analysis pipelines and reagents, are available from the corresponding authors on reasonable request. Source data are provided with this paper.

Code availability

All software and bioinformatic tools used in the present study are publicly available.

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Acknowledgements

We thank H. Leitch for critical reading of the manuscript, and M. Montagner, S. Dupont and the Martello laboratory for their discussions and suggestions. We thank P. Martini for help with next-generation sequencing data analyses and D. De Stefani for technical help with the mitochondrial assays. We thank A. Simeone (Institute of Genetics and Biophysics, CNR, Naples, Italy) for the Otx2-null ESCs. We thank F. Caicci and A. Dinarello for electron microscopy acquisition and technical support. The J.N. laboratory is supported by BBSRC grant no. RG77233. The G.M. laboratory is supported by grants from the Giovanni Armenise–Harvard Foundation, the Telethon Foundation (grant no. TCP13013) and an ERC Starting Grant (MetEpiStem). The S.O. laboratory is supported by grants from Associazione Italiana Ricerca sul Cancro (grant no. AIRC -IG 2017 Id. 20240), the Telethon Foundation (grant no. GGP19201A) and by PRIN 2017. The N.M. laboratory is supported by grants from the Giovanni Armenise–Harvard Foundation, Intramural Transition grant from Università degli Studi di Milano, European Foundation for the Study of Diabetes/Lilly Programme 2015, Associazione Italiana Ricerca sul Cancro (grant no. AIRC -IG 2019 Id. 23127), MIUR Progetto Eccellenza to Department of Pharmacological and Biomolecular Sciences (DiSFeB), University of Milan, Italy.

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Authors

Contributions

G.M., N.M. and S.O. designed the study. R.M.B. and L.D. performed the ESC culture, molecular characterization and functional assays and visualization. V.P. and L.D. performed the MeDIP–qPCR. R.M.B., V.P. and S.R. performed the RRBS. R.M.B. and S.R. performed the western blots. A.L. and D.I. performed the RRBS integrated analysis. M. Arboit and L.D. performed the RNA-seq analyses. R.M.B., S.P. and M. Audano performed the metabolomic analyses. R.M.B., V.P., V.G. and D.T. performed the nucleotide mass spectrometry. P.G. performed the proteomics. M.E.S. and G.R. performed the mitochondrial and nuclear fractionations. L.D. and G.G.S. performed the single-cell RNA-seq analyses. T.L., T.B. and J.N. performed the embryo dissections and single-cell RNA-seq library preparations. G.M. wrote the manuscript with input from all authors. G.M., N.M. and S.O. supervised the study.

Corresponding authors

Correspondence to Nico Mitro or Salvatore Oliviero or Graziano Martello.

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The authors declare no competing interests.

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Peer review information Nature Genetics thanks Heather Christofk, Christian Frezza, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Dnmt3a/b control 5mC levels downstream of LIF–Stat3.

a, Distribution of DNA methylation levels at CpG islands in S3+/+ cells cultured in Serum LIF, 2i or 2iLIF and S3-/- cells in 2iLIF. b, Gene expression analysis in RGd2 cells in 2i with or without LIF. Socs3 was used as a control of LIF–Stat3 activation. Bars: mean of n = 2 biological replicates.c, Proteomics data from S3+/+ and S3-/- cells in 2iLIF. Yellow and blue dots indicate respectively proteins that are more or less abundant (difference > 1 or < -1, p-value < 0.05) in S3+/+ relative to S3-/-. n = 5 biological replicates. d, Western blot of E14 mES cells and of Dnmt3a KO, Dnmt3b KO, and Dnmt3a/b double KO cells (two clones for each mutant genotype) in Serum LIF. Two E14 samples are loaded on the right and left for each KO cell line. B-ACTIN used as a loading control. Representative images of n = 2 independent experiments. e, Distribution of DNA methylation levels at CpG islands in E14 mES cells in 2i or 2iLIF and two clones of Dnmt3a/b double KO mES cells in 2i.f, Gene expression analysis of S3+/+ cells cultured in 2iLIF transiently expressing an Empty Vector, Dnmt3a (two isoforms, Dnmt3a1 and Dnmt3a2 – as previously identified in73), Dnmt3b, or the three genes simultaneously (Dnmt3a1/a2/b OE). Bars: mean ± s.e.m. of n = 3 independent experiments, shown as dots. g, Anti-5mC immunofluorescence on S3+/+ in 2i and 2iLIF, and Dnmt3a1 OE, Dnmt3a2 OE, Dnmt3b OE, and Dnmt3a1/a2/b triple OE cells in 2iLIF. Violin plots of an average of 89 nuclei per sample. n = 4 experiments. h, Gene expression analysis of S3+/+ cells in 2iLIF stably expressing shRNA to knock-down Tet1 and Tet2 simultaneously or a scrambled control shRNA. Bars: mean ± s.e.m. of n = 4 experiments. i, Anti-5mC immunofluorescence on S3+/+ in 2iLIF transiently expressing a scrambled control shRNA and shRNA against Tet1/Tet2. Violin plots of an average of 78 nuclei per sample. n = 4 experiments.All violin and boxplots indicate the 1st, 2nd and 3rd quartiles, with whiskers indicating minimum and maximum value. All p-values calculated by two-tailed unpaired T-test. Scale bars: 20μm.

Source data

Extended Data Fig. 2 Impact of LIF–Stat3 and Dnmt3a/b on genome methylation.

a, MeDIP-qPCR of repetitive elements in S3+/+ and S3-/- cells. Mock immunoprecipitations with a non-specific IgG antibody served as negative controls. Mean of 2 experiments, shown as dots. b, Volcano plot showing the significant differentially methylated CpG sites (q-value < 0.01, difference > 10% or < 10%) between S3+/+ 2i and S3+/+ 2iLIF cells, out of 1,327,475 detected sites. c, d Scatter plot showing the mutual changes in expression and DNA methylation at active promoters (c) and enhancers (d) between S3+/+ 2i and S3+/+ 2iLIF cells. Red dots: genes for which both changes were statistically significant (q-value < 0.01). e, Scatter plot comparing effects on transcription of the absence of LIF (S3+/+ 2i) and the absence of Stat3 (S3-/- 2iLIF). Pearson’s correlation coefficient (R) and corresponding p-value are indicated in the panel. f, Volcano plot showing the significant differentially methylated CpG sites (q-value < 0.01, difference > 10% or < -10%) between E14 2i and E14 2iLIF cells, out of 1,084,350 detected sites. g, CpG methylation changes caused by LIF addition (y axis) or by Dnmt3a/b deletion (x axis, Dnmt3a/b dKO.1). Dots indicate all CpG sites covered (sequencing depth >10x) in at least one technical replicate of each sample; blue dots: hypomethylated sites (q-value < 0.01, difference < -10 %). h, Volcano plot showing the significant differentially methylated CpG sites between Dnmt3a/b dKO.1 and E14 cells cultivated in 2i.i, CpG methylation changes caused by LIF (y axis) or by Dnmt3a/b deletion (x axis, Dnmt3a/b dKO.2), as described in panel g. j, Volcano plot showing the significant differentially methylated CpG sites between Dnmt3a/b dKO.2 and E14 cells cultivated in 2i. k, Venn diagram of CpG sites whose methylation status is dependent on either LIF (light blue) or Dnmt3a/b (red) or on both (grey intersection), for an independent mutant Dnmt3a/b dKO clone (Dnmt3a/b dKO.2).

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Extended Data Fig. 3 Effect of Stat3 inactivation on imprinted transcripts.

a, MeDIP-qPCR of two control regions for DNA methylation change (Gapdh as negative and H19 as positive control). Mock immunoprecipitations with a non-specific IgG antibody served as negative controls. Mean ± s..e.m of 4 experiments for Gapdh and mean of 2 experiments for H19, shown as dots. b, Differentially Methylated Regions and associated imprinted genes. Table reports Differentially Methylated Regions (DMRs) analyzed by RRBS with associated coordinates (reference genome: mm10); information about these DMRs in mouse genome was collected from three different databases (WAMIDEX https://atlas.genetics.kcl.ac.uk/; MouseBook - Imprinting Loci https://www.mousebook.org/; Geneimprint http://geneimprint.com/site/genes-by-species.Imprinted genes whose expression is controlled by the same DMR are grouped accordingly and indicated in the second column of the table. For each imprinted gene, fourth column reports the expected effect on gene expression - either upregulation or downregulation - caused by methylation deposition at the associated DMR (data from literature). The last column of the table shows observed expression levels (RNAseq data) of each imprinted gene in S3-/- cells, were hypermethylation was detected at the corresponding DMR (see Fig. 2f). c, Pie charts showing the number of up- and down-regulated genes (q-value < 0.01, Benjamini-Hochberg adjustment and log2 FC > 1 or < -1) in S3-/- cells with respect to S3+/+ cells among all expressed genes (left), or among all expressed imprinted genes (right).

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Extended Data Fig. 4 Modulating mitochondrial activity affects 5mC levels.

a, Anti-5mC immunofluorescence on S3+/+ cells in 2i or 2iLIF and S3-/- cells in 2iLIF treated with EdU for 4 h. Violin plots show the distribution of an average of 67 nuclei per sample; one representative experiment is shown for each condition. b, Anti-5mC immunofluorescence on S3+/+ cells treated with Rotenone or Antimycin A. Violin plots show the distribution of an average of 74 nuclei per sample. 3 independent experiments shown as individual violins. c, Anti-5mC immunofluorescence on E14 in 2iLIF and 2i, and on Dnmt3a/b double KO cells in 2iLIF, treated with Vehicle, Rotenone or Antimycin A. Violin plots show the distribution of an average of 183 nuclei per sample. 3 experiments shown as individual violins. d, Confocal images of S3+/+, S3-/- cells and MitoS3.A/B clones stained with anti-Stat3 and anti-Atad3 antibodies. Representative images of 3 independent experiments. e, Electron Microscopy images of STAT3 protein stained by Diaminobenzidine photooxidation method, in S3-/- and MitoS3.A cells. Representative images of 2 experiments. M, mitochondria; N, nucleus. f, Expression analysis of Socs3 in S3+/+, S3-/- cells and MitoS3.A/B clones in 2iLIF. Bars: mean of n = 2 experiments, shown as dots. g, (Left) Western blot of S3+/+, S3-/- cells and MitoS3.A and MitoS3.B clones in 2iLIF. LAMIN B: loading control. (Right) Western blot of total lysates or mitochondrial and nuclear fractions. The nuclear protein LAMIN B and mitochondrial marker TIM23 confirmed successful nuclear and mitochondrial isolation. Representative images of 2 independent experiment. h, Oxygen consumption rate measured by Seahorse extracellular flux assay of S3+/+, S3-/- and MitoS3.A/B clones cultured in 2iLIF. Mean and S.D. of n = 5 biological replicates is shown. All violin and boxplots indicate the 1st, 2nd and 3rd quartiles, with whiskers indicating minimum and maximum value. All p-values calculated by two-tailed unpaired T-test. Scale bars: 20μm.

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Extended Data Fig. 5 Metabolic reconfiguration following Stat3 deletion.

a, Diagram representing mass isotopomer distribution (MID) of OAA, Citrate and αKG in both oxidative and reductive Glutamine pathways; MID was analysed following 8 h of metabolic tracing with [U-13C5]-Glutamine. Orange box: mitochondrion. Full circles: 13C-labeled carbons. Color scale outlines the comparison between MID profile in S3-/- relative to S3+/+for n = 6 biological replicates; blue: isotopomers (or biochemical pathways) under-represented is S3-/- cells; red: isotopomers or pathways over-represented in S3-/- cells. Each isotopomer is corrected for natural isotope abundances. b, Metabolic tracing analysis of different isotopomers of TCA cycle intermediates (Succinate, Oxaloacetate, Citrate and αKG) using [U-13C5]-Glutamine. Barplot represents mass isotopomer distribution (MID %) at 3 different time points (2 h, 4 h, 8 h). Black circles: 13C‐labeled carbons. Bars: mean ± s.e.m of n = 6 biological replicates. * p-value<0.05, two-tailed unpaired T-test. Each isotopomer is corrected for natural isotope abundances. c, Expression of IDH1, measured by RT q-PCR and RNAseq in S3+/+ and S3-/- cells. Bars: mean of n = 2 biological replicates. d, Gene expression analysis of two Hif1a targets in S3+/+ cells cultured in 2iLIF in normoxia (high O2–21%), in hypoxia (low O2, 21%), or in normoxia with the addition of αKG or DM-αKG. Bars: indicate mean ± s.e.m. of n = 7 experiments for high O2 and low O2, and n = 4 for treatments with αKG and DM-αKG, shown as dots.

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Extended Data Fig. 6 Mitochondrial Stat3 slows down ESC differentiation.

Gene expression analysis by RT–qPCR of S3+/+, S3-/- and MitoS3.A/B clones cultured with 2iLIF or without 2iLIF for 24 h or 48 h. Data show expression of Imprinted genes a, Mesoderm b, Ectoderm c, and PGCs d, markers that are more readily induced in S3-/- and MitoS3.A/B clones rescues this effect. Beta-actin served as an internal control. Bars indicate mean ± s.e.m. of n = 3 independent experiments, shown as dots. Two-tailed unpaired T-test relative to S3-/- for each time point.

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Extended Data Fig. 7 Stat3 regulates transcripts associated to differentially methylated genomic features.

a, Left: boxplot reporting expression levels of genes down-regulated in S3-/- cells relative to S3+/+ cells (Fig. 7a, blue dots) and differentially methylated at promoter regions (Fig. 2b). Right: boxplot reporting expression levels of genes up-regulated in S3-/- cells with respect to S3+/+ cells (Fig. 7a, yellow dots) and with differential methylation at promoter regions (Fig. 2b). Each boxplot shows 1st, 2nd and 3rd quartile. Whiskers shows minimum and maximum values. Y axis represents mean-normalized TPM values for S3+/+, S3-/- and MitoS3.A and MitoS3.B) in two different conditions: following stable culturing of cells in 2iLIF (light color) and after 48 h of 2iLIF withdrawal from culture medium (dark color). b, Boxplot reporting expression levels of genes down-regulated (left) or up-regulated (right) in S3-/- cells relative to S3+/+ cells and differentially methylated at enhancer regions (Fig. 2c), as described above. c, Boxplot reporting expression levels of genes down-regulated (left) or up-regulated (right) in S3-/- cells relative to S3+/+ cells and differentially methylated at the associated DMR (Fig. 2f), as described above. d, Merge of genes contained in boxplots shown in Extended Data Fig. 7a–c.

Extended Data Fig. 8 Accelerated progression of Stat3 null embryos.

a, Volcano plot of genes differentially expressed between S3-/- and S3+/+ cells at E3.5. Red and blue dots indicate respectively transcripts that are upregulated or downregulated (log2 FC > 0.7 or FC < -0.7 respectively, q-value < 0.1) in S3-/- cells relative to S3+/+ cells. b, Diffusion pseudotime of E3.5 cells and the PrE gene signature computed with R package “destiny" (http://bioinformatics.oxfordjournals.org/content/32/8/1241) using all the expressed genes as input list. P-value calculated with two-tailed Mann-Whitney test. c, PCA plot computed with all the expressed genes. Colors represent different lineages/genotypes (left panel) or ratio between Gata6 and Nanog expression (right panel). d, Volcano plot of genes differentially expressed between S3-/- and S3+/+ cells at E3.75. Red and blue dots indicate respectively transcripts that are upregulated or downregulated (log2 FC > 0.7 or FC < - 0.7 respectively, q-value < 0.1) in S3-/- cells relative to S3+/+ cells. e, Fraction of identity between E3.75 EPI(left panel)/PrE(right panel) and E3.5 ICM, E4.5 EPI, E4.5 PrE, E5.5 EPI and E6.5 EPI stages computed with all the expressed genes. P-value calculated with two-tailed Mann-Whitney test.All boxplot shows 1st, 2nd and 3rd quartile. Whiskers show minimum and maximum values.

Extended Data Fig. 9

Diagram summarizing how mitochondrial Stat3 affects nuclear transcription.

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Betto, R.M., Diamante, L., Perrera, V. et al. Metabolic control of DNA methylation in naive pluripotent cells. Nat Genet 53, 215–229 (2021). https://doi.org/10.1038/s41588-020-00770-2

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