Central to understanding cellular behaviour in multi-cellular organisms is the question of how a cell exits one transcriptional state to adopt and eventually become committed to another. Fibroblast growth factor-extracellular signal-regulated kinase (FGF -ERK) signalling drives differentiation of mouse embryonic stem cells (ES cells) and pre-implantation embryos towards primitive endoderm, and inhibiting ERK supports ES cell self-renewal1. Paracrine FGF–ERK signalling induces heterogeneity, whereby cells reversibly progress from pluripotency towards primitive endoderm while retaining their capacity to re-enter self-renewal2. Here we find that ERK reversibly regulates transcription in ES cells by directly affecting enhancer activity without requiring a change in transcription factor binding. ERK triggers the reversible association and disassociation of RNA polymerase II and associated co-factors from genes and enhancers with the mediator component MED24 having an essential role in ERK-dependent transcriptional regulation. Though the binding of mediator components responds directly to signalling, the persistent binding of pluripotency factors to both induced and repressed genes marks them for activation and/or reactivation in response to fluctuations in ERK activity. Among the repressed genes are several core components of the pluripotency network that act to drive their own expression and maintain the ES cell state; if their binding is lost, the ability to reactivate transcription is compromised. Thus, as long as transcription factor occupancy is maintained, so is plasticity, enabling cells to distinguish between transient and sustained signals. If ERK signalling persists, pluripotency transcription factor levels are reduced by protein turnover and irreversible gene silencing and commitment can occur.
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The microarray, ChIP–seq and RNA-seq data used in this study have been deposited in the Gene Expression Omnibus under accession number GSE132444. The mass spectrometry proteomics data have been deposited with the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD008964 and PXD012573.
Chazaud, C., Yamanaka, Y., Pawson, T. & Rossant, J. Early lineage segregation between epiblast and primitive endoderm in mouse blastocysts through the Grb2–MAPK pathway. Dev. Cell 10, 615–624 (2006).
Canham, M. A., Sharov, A. A., Ko, M. S. H. & Brickman, J. M. Functional heterogeneity of embryonic stem cells revealed through translational amplification of an early endodermal transcript. PLoS Biol. 8, e1000379 (2010).
Levine, M., Cattoglio, C. & Tjian, R. Looping back to leap forward: transcription enters a new era. Cell 157, 13–25 (2014).
Whyte, W. A. et al. Enhancer decommissioning by LSD1 during embryonic stem cell differentiation. Nature 482, 221–225 (2012).
Chen, X. et al. Integration of external signaling pathways with the core transcriptional network in embryonic stem cells. Cell 133, 1106–1117 (2008).
Sturm, O. E. et al. The mammalian MAPK/ERK pathway exhibits properties of a negative feedback amplifier. Sci. Signal. 3, ra90 (2010).
Hamilton, W. B. & Brickman, J. M. Erk signaling suppresses embryonic stem cell self-renewal to specify endoderm. Cell Rep. 9, 2056–2070 (2014).
Sokolik, C. et al. Transcription factor competition allows embryonic stem cells to distinguish authentic signals from noise. Cell Syst. 1, 117–129 (2015).
Tan, F. E. & Elowitz, M. B. Brf1 posttranscriptionally regulates pluripotency and differentiation responses downstream of Erk MAP kinase. Proc. Natl Acad. Sci. USA 111, E1740–E1748 (2014).
Yeo, J.-C. et al. Klf2 is an essential factor that sustains ground state pluripotency. Cell Stem Cell 14, 864–872 (2014).
Kim, M. O. et al. ERK1 and ERK2 regulate embryonic stem cell self-renewal through phosphorylation of Klf4. Nat. Struct. Mol. Biol. 19, 283–290 (2012).
Tee, W.-W., Shen, S. S., Oksuz, O., Narendra, V. & Reinberg, D. Erk1/2 activity promotes chromatin features and RNAPII phosphorylation at developmental promoters in mouse ESCs. Cell 156, 678–690 (2014).
Williams, L. H. et al. Pausing of RNA polymerase II regulates mammalian developmental potential through control of signaling networks. Mol. Cell 58, 311–322 (2015).
Min, I. M. et al. Regulating RNA polymerase pausing and transcription elongation in embryonic stem cells. Genes Dev. 25, 742–754 (2011).
Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013).
Loh, K. M. & Lim, B. A precarious balance: pluripotency factors as lineage specifiers. Cell Stem Cell 8, 363–369 (2011).
Carlson, S. M. et al. Large-scale discovery of ERK2 substrates identifies ERK-mediated transcriptional regulation by ETV3. Sci. Signal. 4, rs11 (2011).
Williams, M. R. et al. The role of 3-phosphoinositide-dependent protein kinase 1 in activating AGC kinases defined in embryonic stem cells. Curr. Biol. 10, 439–448 (2000).
Endo, S., Satoh, Y., Shah, K. & Takishima, K. A single amino-acid change in ERK1/2 makes the enzyme susceptible to PP1 derivatives. Biochem. Biophys. Res. Commun. 341, 261–265 (2006).
Okuzumi, T. et al. Synthesis and evaluation of indazole based analog sensitive Akt inhibitors. Mol. Biosyst. 6, 1389–1402 (2010).
van den Berg, D. L. C. et al. An Oct4-centered protein interaction network in embryonic stem cells. Cell Stem Cell 6, 369–381 (2010).
Yin, J.-W. & Wang, G. The Mediator complex: a master coordinator of transcription and cell lineage development. Development 141, 977–987 (2014).
Allen, B. L. & Taatjes, D. J. The Mediator complex: a central integrator of transcription. Nat. Rev. Mol. Cell Biol. 16, 155–166 (2015).
Ito, M., Yuan, C. X., Okano, H. J., Darnell, R. B. & Roeder, R. G. Involvement of the TRAP220 component of the TRAP/SMCC coactivator complex in embryonic development and thyroid hormone action. Mol. Cell 5, 683–693 (2000).
Anderson, K. G. V. et al. Insulin fine-tunes self-renewal pathways governing naive pluripotency and extra-embryonic endoderm. Nat. Cell Biol. 19, 1164–1177 (2017).
Tarkowski, A. K. Experiments on the development of isolated blastomers of mouse eggs. Nature 184, 1286–1287 (1959).
Mintz, B. Formation of genetically mosaic mouse embryos, and early development of “lethal (t 12/t 12)-normal” mosaics. J. Exp. Zool. 157, 273–292 (1964).
Rossant, J. & Lis, W. T. Potential of isolated mouse inner cell masses to form trophectoderm derivatives in vivo. Dev. Biol. 70, 255–261 (1979).
Grabarek, J. B. et al. Differential plasticity of epiblast and primitive endoderm precursors within the ICM of the early mouse embryo. Development 139, 129–139 (2012).
Pisco, A. O., d’Hérouël, A. F. & Huang, S. Conceptual confusion: the case of epigenetics. Preprint at bioRxiv https://doi.org/10.1101/053009 (2016).
Sharova, L. V. et al. Database for mRNA half-life of 19 977 genes obtained by DNA microarray analysis of pluripotent and differentiating mouse embryonic stem cells. DNA Res. 16, 45–58 (2009).
Ying, Q.-L., Stavridis, M., Griffiths, D., Li, M. & Smith, A. Conversion of embryonic stem cells into neuroectodermal precursors in adherent monoculture. Nat. Biotechnol. 21, 183–186 (2003).
Francavilla, C. et al. Functional proteomics defines the molecular switch underlying FGF receptor trafficking and cellular outputs. Mol. Cell 51, 707–722 (2013).
Sharov, A. A., Schlessinger, D. & Ko, M. S. H. ExAtlas: An interactive online tool for meta-analysis of gene expression data. J. Bioinform. Comput. Biol. 13, 1550019 (2015).
Dobin, A., & Gingeras, T. R. Mapping RNA-seq reads with STAR Curr. Protoc. Bioinformatics 51, 11.14.1–11.14.19 (2015).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Feng, J., Liu, T., Qin, B., Zhang, Y. & Liu, X. S. Identifying ChIP–seq enrichment using MACS. Nat. Protocols 7, 1728–1740 (2012).
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
Tiago, F., et al. Reorganization of enhancer patterns in transition from naive to primed pluripotency. Cell Stem Cell 14, 838–853.
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).
Kelstrup, C. D., Young, C., Lavallee, R., Nielsen, M. L. & Olsen, J. V. Optimized fast and sensitive acquisition methods for shotgun proteomics on a quadrupole orbitrap mass spectrometer. J. Proteome Res. 11, 3487–3497 (2012).
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
Boroviak, T. et al. Lineage-specific profiling delineates the emergence and progression of naive pluripotency in mammalian embryogenesis. Dev. Cell 35, 366–382 (2015).
We thank M. Thomson for the NANOG–eGFP ES cells, T. Kunath for Erk2-KO cells, N. Festuccia for Esrrb-KO cells, H.H. Ng for the KLF2 and TFCP2L1 antibodies, the Brickman laboratory members for critical discussions, Y. Spector for sequencing assistance, H. Neil, M. Michaut and the DanStem Genomics Platform for technical expertise, support, and the use of instruments, S. Pozzi, N. Festuccia and P. Navarro Gil for advice on ChIP protocols, K. Stewart-Morgan for help with ATAC-seq, A. Azad and J. A. R. Herrera for bioinformatics advice and P. van Dieken for technical support and proof reading. This work was funded by grants from the Novo Nordisk Foundation, Danish Council for Independent Research (8020-00100B), Danish National Research Foundation (DNRF116) and Human Frontiers in Science (RGP0008/2012). The Novo Nordisk Foundation Centers for Stem Cell Biology and Protein Research are supported by a Novo Nordisk Foundation grant numbers NNF17CC0027852 and NNF14CC0001. R.S.M. is supported by a fellowship from the Lundbeck Foundation (R303-2018-2939).
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Peer review information Nature thanks Charles Danko and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Extended data figures and tables
Extended Data Fig. 1 ERK induction by cRAF-ERT2 mimics endogenous FGF activity and directly regulates ES cell transcription.
a, A schematic representation of the inducible cRAF-ERT2 construct. Versions with and without the FKBP(L106P) were used in this study and were found to be identical with respect to leakiness and induction. Stable cell lines were generated by random integration—all clones were screened for homogenous induction and maintained in selection for routine culture to prevent transgene variegation. b, Immunofluorescence analysis of pERK following 30 min of 4OHT treatment in cRAF-ERT2-expressing ES cells showing homogenous induction of ERK phosphorylation. Data are representative of more than three biologically independent samples. c, Western blot showing loss of ERK and p90RSK phosphorylation following a 2 h induction and a subsequent 30-min treatment with 1 μM MEKi. All cell treatments were performed without medium changes to avoid confounding effects of serum stimulation. Data are representative of more than three biologically independent samples. d, Immunofluorescence analysis of pERK in Fgf4−/− ES cells expressing cRAF-ERT2, stimulated with either recombinant FGF4 (40 ng ml−1) or 4OHT (250 nM) for the indicated times. The arrow indicates a cell with persistent pERK staining in FGF4-stimulated cells. Data are representative of three biologically independent samples. e, Schematic of a single ERK pulse. f, Gene ontology (GO) analysis of ERK-regulated genes at 8 h. Data are derived from two biologically independent samples. g, Comparison of the ERK-dependent half-life of wild-type NANOG and NANOG–eGFP showing no significant differences resulting from the eGFP tag. ERK activity was induced and in wild-type or NANOG–eGFP cells expressing cRAF-ERT2 and NANOG expression was monitored at 3 or 6 h. The half-life was calculated as tx(log(0.5))/log(N(tx)/N(t0)), where tx is the duration of treatment, N(tx) is protein concentration at time tx and N(t0) is initial protein concentration, and significance was tested using a two-tailed Student’s t-test. Data are mean ± s.e.m., n = 6 derived from 3 biologically independent samples measured at 3 and 6 h. h, ChIP–qPCR analysis of changes in H3K27me3 deposition across the NANOG locus between 24 and 36 h of ERK induction, significant increases between 24 and 36 h are denoted by *P = 0.05, **P = 0.02 (one tailed student t-test; data are mean ± s.e.m., n = 3 biologically independent samples). i, A heat map showing effective suppression of a panel of ERK-induced genes on treatment in the presence of actinomycin D. Values are log2-transformed and displayed between the range of −5 and 5. n = 3 biologically independent samples. j, A box plot comparing the mRNA degradation rates of ERK target genes following a 4 h treatment with actinomycin D, with (4OHT) or without (EtOH) ERK activation, showing no significant contribution from ERK (two-sided Wilcoxon test). n = 415; data are derived from n = 3 (4OHT) and n = 2 (EtOH) biologically independent samples. Boxes show median, first and third quartiles, whiskers show 1.5× IQR and outliers are shown as black dots. k, PCA of gene expression in cells stimulated with ERK (4OHT) for 6 h with or without the proteasome inhibitor MG132. PC1 includes the variance caused by proteasomal inhibition, whereas PC2 captures the effect of ERK stimulation. n = 3 biologically independent samples. l, Scaled gene expression values for either repressed genes (top) or induced genes (bottom) that contribute to the variance in PC2 overlaid with the respective eigenvectors from k. The correlation threshold was set at 0.7. PC analysis and correlation scores were derived using ExAtlas. Data are derived from three biologically independent samples. m, Expression changes in NANOG–eGFP levels in response to ERK stimulation in cells expressing wild-type KLF2 or KLF4, or their respective putative ERK-regulated phosphorylation-site mutants (serine to alanine). Stable cell lines were derived for each gene and an empty vector served as a negative control. Expression of each protein (wild type and S>A mutant) was confirmed by western blot analysis (data not shown). A modest, but significant reduction in the magnitude of NANOG–eGFP repression was observed only in cells expressing KLF4(S123A) at 4 h (one-tailed Students t-test P = 0.02). Data are mean ± s.e.m., n = 3 biologically independent samples. n, RNA-seq time-course analysis of the first 4 h of ERK induction with robust mRNA differences only being observed at 4 h (top; y axis represent the number of significantly changing genes) and heat map of row-scaled values (bottom). n = 3 biologically independent samples.
Extended Data Fig. 2 ERK regulates RNAPII and TBP binding to control nascent transcription independently of PRC2 activity.
a, Quantification of the changes in intronic reads of the RNA-seq time course shown in Extended Data Fig. 1n, showing rapid repression of nascent transcription of a panel of transcription factors. The curves represent a cubic spline interpolation of the discrete points (using the MATLAB function cscvn). The maximal fold changes are for the 4 h period tested and are taken from the fitted spline curves. n = 3 biologically independent samples. b, RT–qPCR analysis of nascent (intronic) RNA for the indicated genes in the presence or absence of the translation inhibitor cycloheximide. Cells were pre-treated with cycloheximide (20 µg ml−1) for 30 min before 4OHT addition. Data are mean ± s.e.m., n = 3 biologically independent samples. c, Box plots showing H3K27me3 deposition across gene bodies of ERK induced or repressed genes following 2 h ERK stimulation. No significant changes in response to ERK were observed (significance was tested using two-permutation tests with 2,000 simulations). n = 62,426 (global), n = 882 (induced) and n = 1,362 (repressed). Data are derived from two biologically independent samples. Boxes show median, first and third quartiles, whiskers show 1.5× IQR and outliers are shown as black dots. d, Immunofluorescence analysis showing H3K27me3 staining in cRAF-ERT2-expressing cells treated for 24 h with DMSO or the EZH2 inhibitor EPZ-6438 (EZHi), and subsequently stimulated for 2 h with 4OHT. Data are representative of three biologically independent samples. e, RT–qPCR analysis of a panel of induced and repressed genes showing little dependency on PRC2 enzymatic activity (based on EPZ-6438 treatment) for either induced or repressed genes other than Myc and cFos, both of which showed slightly increased induction in cells depleted of H3K27me3. Two-tailed Students t-test, *P = 0.02, **P = 0.001; Data are mean ± s.e.m., n = 3 biologically independent samples. f, A schematic depicting the strategy to define changes in RNAPII binding. g, A scatter plot showing the correlation of RNAPII binding in 227 differentially bound genes. The differentially bound genes were identified by counting the number of RNAPII ChIP reads that uniquely mapped to gene bodies in the 0 h, 8 h and 8 h + 2 h MEKi conditions. Pairwise comparisons using DESeq2 identified 180 genes with significant changes in RNAPII binding between 8 h and 8 h + 2 h MEKi and 126 between 8 h and 0 h. Concatenation of the two gene lists resulted in 227 genes bodies that show a positive correlation in RNAPII binding (Spearman correlation R = 0.79, P < 2.2 × 10−16) induced by ERK and reversed by inhibition of the pathway. n = 3 (0 h), n = 3 (8 h) and n = 2 (8 h + 2 h MEKi) biologically independent samples. h, Binding profiles of TBP to the TSSs of genes with changing RNAPII (left) and ChIP–seq tracks for the TSS of both Nanog and Spry4 (right). Data are derived from two biologically independent samples. i, A heat map showing the changes in nascent RNA expression of ERK-regulated genes associated with super enhancers (|log2(FC)| > 1, adj. P ≤ 0.01). n = 3 biologically independent samples. Super enhancer gene association was performed using GREAT (http://great.stanford.edu/).
Extended Data Fig. 3 ERK regulates ES cell enhancer activity.
a, RT–qPCR analysing the expression of eRNA at pluripotency super enhancers. Fgf4−/− ES cells were stimulated for either 30 or 90 min with 40 ng ml−1 recombinant FGF4 before analysis. *P < 0.05 and **P < 0.01, two-tailed Student’s t-test; data are mean ± s.e.m., n = 6 independent experiments. b, A scatter plot showing the changes in RNAPII binding and eRNA expression at regulated super enhancers (adj. P ≤ 0.01), showing a high level of correlation between RNAPII binding and eRNA expression in response to ERK (two-sided Spearman's correlation coefficient). n = 3 biologically independent samples. c, A scatter plot showing the changes in H3K27ac and EP300 enrichment at both putative traditional and super enhancers in response to ERK (see materials and methods for further details). ERK activation results in the correlated changes in EP300 binding and H3K27ac deposition at both super enhancers and traditional enhancers (two-sided Spearman's correlation coefficient). n = 636 (activated traditional enhancers), n = 1,726 (repressed traditional enhancers), n = 30 (repressed super enhancers) and n = 27 (activated super enhancers). Data are derived from two biologically independent samples. d, A volcano plot showing the expression pattern of ERK-regulated genes (taken from Fig. 1d, nascent RNA) associated with ERK-regulated enhancers. n = 3 biologically independent samples. e, A stacked bar chart showing the percentage of genes repressed or induced by ERK and associated with repressed (acDOWN) or activated (acUP) enhancers. Eighty-five per cent of genes associated with repressed enhancers are repressed themselves and, similarly, 83% of genes associated with activated enhancers are themselves induced by ERK. Gene association was performed using GREAT (http://great.stanford.edu/) with single-nearest-gene cut-off. f–i, ATAC profiles at ERK regulated traditional enhancers (f, g) and super enhancers (h, i) following 2 h stimulation, showing that changes in chromatin accessibility at traditional enhancers, but not at super enhancers, is reflective of their activity. n = 3 biologically independent samples. j, A scatter plot showing the changes in mRNA and protein levels for a panel of ES cell transcription factors in response to 6 h ERK signalling. All but NANOG show a degree of persistence into early differentiation. n = 3 biologically independent samples. k, mRNA and protein half-lives of a panel of ES cell transcription factors measured by actinomycin D and cycloheximide treatment, respectively. In brief, cells were treated with actinomycin D (1 μM), or cycloheximide (20 μg ml−1) for time periods ranging from 3–6 h. Samples were collected and processed whereupon the respective half-lives were calculated as in extended data Fig. 1g. Data are mean ± s.e.m., n = 3 biologically independent samples. l, Bar chart showing the overlap of SOX2 and ESRRB binding with the list of enhancers defined in c. Overlap was determined using the UpSet module from Intervene. Data are derived from two biologically independent samples. m, Chow–Ruskey diagrams showing overlap of ERK-regulated tranditional enhancers with changing transcription factor binding, showing that early changes are largely maintained at later time points. Graphs are scaled to maximal changes at 8 h for each transcription factor. Data are derived from two biologically independent samples.
Extended Data Fig. 4 Pluripotency transcription factors remain stably bound to super enhancers, are lost from low-affinity binding sites, but are recruited to regions of highly active transcription.
a, b, Box plots showing the changes in EP300 and transcription factor binding at ERK-regulated super enhancers at the indicated times. EP300 shows a higher degree of change at 2 h than transcription factors at 2 or 4 h. *P < 0.01 compared to EP300 (two-sided Wilcoxon test). n = 30 (repressed super enhancers) and n = 27 (activated super enhancers). Data are derived from two biologically independent samples. Boxes show median, first and third quartiles, whiskers show 1.5× IQR and outliers are shown as black dots. c, ChIP–seq tracks of SOX2 and ESRRB at one of the three super enhancers (shown in red) with decreasing binding. Data are representative of two biologically independent samples. d, Motif analysis of ERK-regulated enhancers with decreasing transcription factor binding showing no enrichment for any known transcription factor binding motif. n = 334 (SOX2) and n = 184 (ESRRB). Data are derived from two biologically independent samples. e, GO analysis of enhancers with increased ESRRB (top) and SOX2 (bottom) binding. GO analysis was performed using GREAT; binomial P values are presented. Data are derived from two biologically independent samples. f, A Venn diagram showing a high degree of overlap in the peaks analysed in Fig. 3d. g, Box plots comparing the expression levels (probe intensity) of all ERK-induced genes with genes associated with ESRRB peaks exhibiting increasing binding at 8 h. Genes that show increased transcription factor binding in response to ERK are the most robustly induced in response to ERK, and the magnitude of this expression is not dependent on ESRRB. Two-sided Wilcoxon test (knockout vs rescue), P > 0.9; n = 3 biologically independent samples. Boxes show median, first and third quartiles, whiskers show 1.5× IQR and outliers are shown as black dots.
Extended Data Fig. 5 Erk phosphoproteome includes AKT and AGC kinase sites, but the activity of these kinases is dispensable for transcriptional regulation by ERK.
a, A cartoon outlining the experimental setup for SILAC phosphoproteome profiling. See methods for further information on SILAC labelling conditions. b, GO analysis of Fig. 4a, cluster 2, showing an enrichment in terms associated with transcriptional regulation. FDR values are presented and significance was determined using http://geneontology.org/. Data are derived from two biologically independent samples. c, A schematic depicting the Pdpk1-rescue construct introduced into Pdpk1−/− ES cells. Stable lines were generated through random integration and all clones were tested for homogenous ERK induction and Flag–PDK1 expression. d, Western blot analysis of a time course of ERK induction and subsequent inhibition showing that ERK-regulated phosphorylation of sites that are also known to be co-regulated by AKT, is PDK1 dependent. ERK-mediated phosphorylation of GSK3-β at S9 and dual phosphorylation of RPS6 at S235 and S236 are rescued by the re-expression of PDK1. Data are representative of three biologically independent samples. e, Correlation (two-tailed Pearson correlation) of changes in gene expression in either PDK1-rescue or knockout cells under the indicated conditions showing a high correlation between knockout and rescue lines. n = 3 biologically independent samples. f, Scatter plot showing the expression of genes significantly regulated by ERK (|log2(FC)| > 1, FDR ≤ 0.01) in PDK1 rescued cells compared with knockout cells. No significant difference could be detected between the two cell types. n = 3 biologically independent samples. g, The experimental setup to determine the MEK–ERK dependent ES cell phosphoproteome. Fgf4−/− cells were treated with recombinant FGF4 (40 ng ml−1) for 5 min, whereas ERK2AS-expressing cells were stimulated for 2 h with 4OHT. h, An outline of the strategy to generate ERK2AS-expressing cells. Erk2−/− cells (Erk2 is also known as Mapk1; Erk2 KO ES cells) were rescued by expressing Flag–ERK2(Q103A) from a stably integrated cassette similar to that used for Pdpk1 rescue depicted in c. Subclones were screened and subjected to Erk1 (also known as Mapk3) mutation by CRISPR–Cas9 mutagenesis.
Extended Data Fig. 6 The kinase activity of ERK, targeting proline-directed serines, is essential for its capacity to regulate transcription.
a, A cartoon depicting the various ERK alleles in ERK2AS-expressing ES cells. b, A bar chart showing the suppression of RPS6 phosphorylation (S235/236) by treatment with 2 μM PP1. Data are mean ± s.d. n = 6 biologically independent samples. c, Western blot analysis of ERK1 in ERK2AS-expressing ES cells confirming loss of ERK1 protein. Data are representative of two independent experiments. d, e, Analysis of enriched motifs for both FGF4- and 4OHT-induced sites indicating which are sensitive to inhibition of MEK and ERK, showing that the primary motif in sites sensitive to both is, again, a proline directed serine. FGF4 experiments: n = 3 (DMSO), n = 3 (FGF4), n = 2 (MEKi), n = 3 (FGF4 + MEKi). ERK2AS experiments: n = 3 (DMSO), n = 3; (4OHT), n = 3 (ERK2AS − 4OHT + PP1) and n = 2 (4OHT + MEKi) biologically independent samples. f, Box plots showing the extent to which either MEKi or PP1 treatment can block ERK-dependent transcriptional changes. All sample permutations are significantly different from each other (two-sided Wilcoxon test, P < 2.2 × 10−16). n = 2 (0 h DMSO), n = 3 (0 h PP1), n = 3 (0 h MEKi), n = 3 (2 h DMSO), n = 3 (2 h PP1) and n = 3 (2 h MEKi) biologically independent samples. Boxes show median, first and third quartiles, whiskers show 1.5× IQR and outliers are shown as black dots. g, Quantification of the phosphorylation of the indicated proteins in response to 1 h ERK stimulation in either Erk2−/− cells (EV), or knockout cells rescued with a Flag-ERK2 construct (data are presented as the mean and standard error). n = 3 biologically independent samples. h, RT–qPCR analysis of the expression of the indicated genes following 2 h ERK stimulation in either Erk2−/− cells 2(EV), or knockout cells rescued with a Flag-Erk2 construct. Data are mean ± s.e.m., n = 3 biologically independent samples. i, Venn diagram showing the overlap between ESRRB-interacting proteins with cluster 2.
Extended Data Fig. 7 MED24 is a key target of ERK required for normal transcriptional responses.
a, ERK robustly phosphorylates the Mediator component MED24 on two serines in the C-terminal end of the protein directly adjacent to a hormone receptor-interaction domain; values taken from (Fig. 4a). Data are presented as the mean, n = 2 biologically independent samples. b, Expression values for Med24 at the indicated developmental stages44. c, A schematic outlining the strategy for making Med24-conditional ES cells and where single RNA guides are targeted in the endogenous locus. Med24 expression is maintained by a doxycycline-inducible promoter, whereby stable integration of the cassette can be selected for by either neomycin (top) or hygromycin (bottom). d, e, Western blot analysis of the expression levels of MED24 in wild-type ES cells expressing either construct depicted in c before deletion of endogenous MED24. Selection of exogenous MED24 with neomycin (d) gives slightly higher expression levels than selection with hygromycin (e). Data are representative of two independent experiments. All mutant phenotypes were reproduced in knockout cell lines rescued with either construct. ChIP–seq and transcriptome analysis was performed using cells expressing the neomycin rescue. f, Western blot analysis confirming disruption of endogenous MED24 from hygromycin-selected cells. C14, C15, C2 and C5 are homozygous-mutant cell lines. Data are representative of two independent experiments. g, Western blot analysis confirming disruption of endogenous MED24 from neomycin selected cells. WT1, WT3, WT5 and WT6 are homozygous-mutant cell lines. Data are representative of two independent experiments. h, GO analysis for MED24-bound regions showing that bound regions are associated with genes involved in peri-implantation development. MED24 peaks were located within traditional enhancers (from Extended Data Fig. 3c) and ontologically annotated with GREAT. n = 3 biologically independent samples. i, Motif analysis for MED24-binding regions within repressed and activated enhancers showing enrichment for ESRRB (repressed) and ETS–AP-1-factor (activated) motifs. n = 636 (activated) and 1,726 (repressed). j, Quantification of the levels of NANOG–eGFP expression upon the depletion of MED24. Data are mean + s.e.m., n = 6 biologically independent samples. k, ChIP-qPCR analysis of RNAPII binding to the Nanog enhancer in either wild-type or MED24-knockout cells; enrichment at an unbound region between the proximal enhancer and TSS serves as a negative control. Data are mean + s.e.m., n = 3 biologically independent samples. l, PCA of the nascent transcriptional response in wild-type and MED24-knockout samples following 2 h ERK stimulation. n = 3 biologically independent samples.
Extended Data Fig. 8 Mediator binding is regulated by ERK and is not required for neural specification.
a, Expression levels of eRNA expressed from the Klf4 or Spry4 super enhancers in wild-type or MED24-knockout cells following 2 h ERK activity. Data are mean + s.e.m.; *P = 0.03, **P = 0.006, one-tailed Student’s t-test. Reads were normalized to housekeeping genes. n = 3 biologically independent samples. b, Co-localization analysis of ChIP peaks for ESRRB, MED1 and MED24 showing MED1 is rarely found with ESRRB in absence of MED24. c, A stacked bar chart showing the percentage of all potential enhancers with changes in EP300, MED1 or MED24 following 2 h ERK induction. Changes in cofactor binding range from 10 to 20% of all putative enhancers, indicating that the regulation of binding is selective. Data are derived from two biologically independent samples. d, Box plots showing the binding of Mediator components to repressed and activated traditional enhancers and super enhancers. The magnitude of change relative to EP300 is significantly different at super enhancers (two-sided Wilcoxon test). n = 1,726 (repressed traditional enhancers), n = 636 (activated traditional enhancers), n = 231 (all super enhancers), n = 30 (repressed super enhancers) and n = 27 (activated super enhancers). Data are derived from two biologically independent samples. Boxes show median, first and third quartiles, whiskers show 1.5× IQR and outliers are shown as black dots. e, f, Chow–Ruskey diagrams showing the relative loss (e), or gain (f) of cofactor components from ERK-regulated traditional enhancers. At activated enhancers, the majority of regions with EP300 binding show changes in Mediator association, whereas at repressed enhancers, there is an appreciable number of changes in EP300 binding that appear to occur in the absence of Mediator dissociation. Data are derived from two biologically independent samples. g, h, Motif analysis of regions defined in e and f, showing that regions enriched in ESRRB and ETS–AP-1 motifs are regions where both Mediator and EP300 binding changes in response to ERK. A similar, but less marked effect is observed for canonical pluripotency binding motifs that are also enriched within these regions. n = 367 (increased binding of Mediator and EP300), n = 73 (increased binding of EP300 only), n = 261 (reduced binding of EP300 only) and n = 903 (reduced binding of Mediator and EP300). i, Flow cytometry analysis of the cell surface marker PDGFRA and NANOG–eGFP for wild-type or MED24-knockout cells at day five of neural differentiation. Data are representative of 3 biologically independent samples. j, Immunofluorescence of wild-type or MED24-knockout cells following five days of neural differentiation for the early neural marker NESTIN. Data are representative of three biologically independent samples.
Extended Data Fig. 9 MED24 is specifically required for primitive endoderm specification, but not its expansion or survival.
a, RT–qPCR analysis of ES cell and neural markers following four days of neural differentiation in wild-type and MED24-knockout cells. Data are mean ± s.e.m., n = 3 biologically independent samples. b, Flow cytometry analysis of wild-type or MED24-knockout cells at day five of primitive endoderm differentiation for the cell-surface markers PDGFRA (primitive endoderm) and PECAM1 (ES cell). Data are representative of three biologically independent samples. c, Quantification of flow cytometry analysis for the primitive endoderm-cell-surface marker PDGFRA staining of cells following five days primitive endoderm differentiation. Data are mean + s.e.m.; *P = 0.01, one tailed Students t-test; n = 3 biologically independent samples. d, e, RT–qPCR for either pluripotency or primitive endoderm markers showing both a failure to repress pluripotent transcription and also to induce primitive endoderm markers in MED24-knockout cells. Data are mean + s.e.m.; *P = 0.03, **P = 0.02, ***P = 0.0004 and ****P = 0.00002; two-tailed Students t-test; n = 3 biologically independent samples. f, Quantification of the numbers of Ki67+ nEnd cells with and without MED24. Cells were differentiated towards stable and homogenous endoderm culture whereupon doxycycline was removed to deplete cells of MED24. Analysis was performed after 48 h and no detectable difference in the number of proliferating cells was observed in response to MED24 depletion. Data are mean + s.e.m., n = 3 biologically independent samples. g, As in f, except analysis of cleaved caspase-3 as a marker of apoptosis was used and no MED24 dependent difference in apoptosis was observed. Data are mean + s.e.m., n = 3 biologically independent samples. h, RT–qPCR analysis of the ERK target genes Egr3 and Fosl2 following 2 h activity in MED24 wild type or MED24 (S860A/S871A) rescued Med24−/− cells. A slightly attenuated response to ERK was observed in the induction of two of the most MED24-dependent genes from Fig. 5a when both serines 860 and 871 were mutated to alanine. Data are mean + s.e.m.; *P = 0.04 and **P = 0.01, two-tailed Students t-test; n = 3 biologically independent samples. i, Quantification of flow cytometry analysis for the primitive endoderm cell-surface marker PDGFRA at day five of differentiation in Med24−/− ES cells rescued with either wild-type MED24 or MED24(S860A/S871A). n = 3 (wild type) and n = 2 (S860A/S871A) biologically independent samples.
Extended Data Fig. 10 A model for primitive endoderm priming involving the stable association of transcription factors alongside the reversible reallocation of cofactors and the RNAPII complex.
A cartoon describing the sequence leading to ERK-dependent transcriptional activation, repression and primitive endoderm commitment. ERK activation results in rapid but reversible changes in the binding of RNAPII and associated cofactors at regulated genes, without directly impacting on transcription factor binding in these regions. If the signal is maintained to a point where the activating transcription factors repressed by ERK (specifically pluripotency factors) drop below a minimum threshold, the ability to reform a functionally active transcription complex is lost and terminal differentiation occurs. Similarly, in pluripotent cells, early differentiation genes are marked by the association of transcription factors that enable them to respond rapidly to the induction of ERK signalling, allowing the recruitment of RNAPII with associated cofactors and ensuing transcriptional activation.
Supplementary Figure 1
Uncropped western blots.
Supplementary Figure 2
An example of the standard gating strategy for flow cytometry analysis. Cells are gated based on side scatter (SSC) and forward scatter (FSC). Single cells are then gated based on FSC-width (W) vs FSC-height (H) followed by gating live cells based on DAPI exclusion. Single, viable cells are then analysed for epitope expression.
This file contains Supplementary Tables 1-23 and a guide.
Suppression of Nanog is non-selective. Time lapse analysis of Nanog-EGFP expression following ERK induction. Cells were continuously imaged every 20 minutes for approximately 18hrs.
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Hamilton, W.B., Mosesson, Y., Monteiro, R.S. et al. Dynamic lineage priming is driven via direct enhancer regulation by ERK. Nature 575, 355–360 (2019). https://doi.org/10.1038/s41586-019-1732-z
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