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A transcriptional switch governs fibroblast activation in heart disease

Abstract

In diseased organs, stress-activated signalling cascades alter chromatin, thereby triggering maladaptive cell state transitions. Fibroblast activation is a common stress response in tissues that worsens lung, liver, kidney and heart disease, yet its mechanistic basis remains unclear1,2. Pharmacological inhibition of bromodomain and extra-terminal domain (BET) proteins alleviates cardiac dysfunction3,4,5,6,7, providing a tool to interrogate and modulate cardiac cell states as a potential therapeutic approach. Here we use single-cell epigenomic analyses of hearts dynamically exposed to BET inhibitors to reveal a reversible transcriptional switch that underlies the activation of fibroblasts. Resident cardiac fibroblasts demonstrated robust toggling between the quiescent and activated state in a manner directly correlating with BET inhibitor exposure and cardiac function. Single-cell chromatin accessibility revealed previously undescribed DNA elements, the accessibility of which dynamically correlated with cardiac performance. Among the most dynamic elements was an enhancer that regulated the transcription factor MEOX1, which was specifically expressed in activated fibroblasts, occupied putative regulatory elements of a broad fibrotic gene program and was required for TGFβ-induced fibroblast activation. Selective CRISPR inhibition of the single most dynamic cis-element within the enhancer blocked TGFβ-induced Meox1 activation. We identify MEOX1 as a central regulator of fibroblast activation associated with cardiac dysfunction and demonstrate its upregulation after activation of human lung, liver and kidney fibroblasts. The plasticity and specificity of BET-dependent regulation of MEOX1 in tissue fibroblasts provide previously unknown trans- and cis-targets for treating fibrotic disease.

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Fig. 1: Heart failure reversibility with BET inhibition correlates with myofibroblast state.
Fig. 2: Reversibility of chromatin states in fibroblasts reveals DNA elements that correlate with heart function.
Fig. 3: Chromatin accessibility and nascent transcription identify a cis-element controlling Meox1 expression.
Fig. 4: MEOX1 regulates fibroblast plasticity and profibrotic function.

Data availability

All source data, including sequencing reads and single-cell expression matrices have been deposited in the NCBI’s Gene Expression Omnibus under accession number GSE155882.

Code availability

All scRNA-seq analyses were performed using standard protocols with the Seurat R package (v.2.3.4). Custom codes relevant to the scATAC-seq analysis are available on GitHub (https://github.com/PFPrzytycki/FibroSwitch).

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Acknowledgements

We thank members of the Srivastava laboratory, J. van Bemmel, M. Costa, N. Palpant, W. J. Shim, P. Grote, E. P. Nora, A. A. Rao, A. J. Combes, P. Benaglio and K. N. Ivey and J. Yang for discussion and feedback; and J. Qi, D. Li and L. Sigua for providing JQ1. We acknowledge the UCSF Center for Advanced Technology (CAT), Gladstone Genomics Core and Flow Cytometry Core for their technical support and the Gladstone Animal Facility for support with mouse colonies. M.A. was supported by the Swiss National Science Foundation (P400PM_186704 and P2LAP3_178056). P.F.P. and K.S.P. were supported by NIH P01 HL098707, HL098179, Gladstone Institutes and the San Simeon Fund. R.M. was supported by the NIH R01 AG070154. A. Padmanabhan was supported by the NIH (K08HL157700), Tobacco‐Related Disease Research Program (578649), A. P. Giannini Foundation (P0527061), Michael Antonov Charitable Foundation and Sarnoff Cardiovascular Research foundation. J.G.T. was supported by NIH F32 HL147463. B.G.T. was supported by the American Heart Association (18POST34080175). R.J. was supported by the Burroughs Wellcome Fund and funds from the Allen Foundation and American Heart Association. T.A.M. was supported by NIH R01 HL116848, NIH R01 HL147558, NIH R01 DK119594 and NIH R01 HL150225. T.A.M. and J.G.T. were supported by the American Heart Association (16SFRN31400013). M.G.R. is an investigator with HHMI and was supported by NIH R01 HL150521. S.M.H. was supported by NIH R01 HL127240. D.S. was supported by NIH P01 HL146366, NIH R01 HL057181, NIH R01 HL015100, and by the Roddenberry Foundation, the L.K. Whittier Foundation, Dario and Irina Sattui and the Younger Family Fund. D.S. and T.A.M. were supported by NIH R01 HL127240. This work was also supported by NIH/NCRR grant C06 RR018928 to the Gladstone Institutes.

Author information

Affiliations

Authors

Contributions

M.A., S.M.H. and D.S. conceived the study, interpreted the data and wrote the manuscript. Y.H. performed heart surgeries and echocardiography. M.A., A. Padmanabhan and C.Y.L. performed JQ1 injections. M.A., A. Padmanabhan and Q.D. collected heart tissues and isolated cardiac cells for subsequent scRNA-seq or scATAC-seq. S.S.R. prepared chromium libraries. M.A. and G.A. analysed bulk RNA-seq. M.A., C.A.G. and G.A. analysed scRNA-seq. A.C.S., R.L.-S., L.L. and R.J. performed and analysed Picrosirius red staining. P.F.P. and K.S.P. analysed scATAC-seq and developed computational methods. R.M. and M.G.R. performed and analysed PRO-seq and 4C. M.A. and L.Y. generated all of the immortalized fibroblast lines. M.A., L.Y., F.F. and N.S. performed knockdown experiments and RT–qPCR analyses. M.A. and A.C.S. performed αSMA immunofluorescence. J.G.T. and T.A.M. performed collagen-contraction and proliferation studies on primary cardiac fibroblasts. M.A., B.G.T. and A. Pelonero performed and analysed ChIP–seq.

Corresponding authors

Correspondence to Saptarsi M. Haldar or Deepak Srivastava.

Ethics declarations

Competing interests

D.S. is a scientific co-founder, shareholder and director of Tenaya Therapeutics. S.M.H. is an executive, officer and shareholder of Amgen, a scientific co-founder and shareholder of Tenaya Therapeutics, and serves on the scientific advisory board of DZHK (German Centre for Cardiovascular Research).  K.S.P. is a shareholder of Tenaya Therapeutics. T.A.M. is on the scientific advisory board of Artemes Bio, Inc., received funding from Italfarmaco for an unrelated project, and has a subcontract from Eikonizo Therapeutics related to an SBIR grant from the National Institutes of Health (HL154959).

Additional information

Peer review information Nature thanks Jeffery Molkentin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Single-cell transcriptional landscape of non-cardiomyocytes in heart failure during intermittent exposure to BET bromodomain inhibition.

a, Venn diagram showing overlap of TAC-induced and JQ1-suppressed genes (log2[FC] > 0.5; adjusted P < 0.05; false-discovery rate-adjusted, Benjamini–Hochberg correction) between bulk RNA-seq from undissociated left ventricle tissue5 and extracted cardiomyocytes. b, Heat map showing the top-5 markers per cluster in the scRNA-seq data. Total cells, n = 35,551 in 9 clusters. c, UMAP plots showing cluster identity of all cells (n = 35,551) and expression of Dcn, Postn, Ctgf, Lyz2 and Fabp4. d, e, UMAP plot coloured by sample identity of myeloid (d, n = 7,986) and endothelial (e, n = 10,672) cells.

Extended Data Fig. 2 Reversible effect of JQ1 exposure on the transcriptional signature of baseline and stressed fibroblasts.

a, Expression of known fibroblast stress-related genes shown as a UMAP feature plots in fibroblasts (total cells, n = 13,937). b, Expression by sample of known fibroblast stress-related genes shown as violin plots in fibroblasts. y axes, normalized UMI levels. c. Dot plots showing expression (avg.exp.scale) and cell percentages (pct.exp) of the top differentially expressed marker genes between samples. d, Percentages of the 260 genes upregulated in fibroblasts in TAC versus sham that are significantly downregulated in TAC JQ1 versus TAC (blue bar) and upregulated in TAC JQ1 withdrawn versus TAC JQ1 (yellow bar). e, Percentages of the 194 genes significantly downregulated in TAC versus sham that are significantly upregulated in TAC JQ1 versus TAC (blue bar) and downregulated in TAC JQ1 withdrawn versus TAC JQ1 (yellow bar). f, Violin plots showing the normalized expression score across fibroblast samples of the 194 genes significantly downregulated in TAC versus sham and associated top GO terms (Fisher’s exact test).

Extended Data Fig. 3 Fibroblast subclusters associated to stress-related gene programs are depleted in sham and TAC JQ1 cells.

a, UMAP plot of fibroblasts coloured by sample identity. n = 13,937. b, Left, UMAP plot of fibroblast subclusters coloured by cluster identity. Right, a tree diagram showing the cluster relationship. Total cells, n = 13,937. c, Histograms showing the percentage of each sample in each fibroblast cluster. d, Heat map showing the top 10 markers per fibroblast cluster in the scRNA-seq data. Total cells, n = 13,937 in 9 clusters. e, Postn expression in fibroblasts by cluster as violin plots. y axes, normalized UMI levels. f, Comparative GO term analysis (Fisher’s exact test) between fibroblast clusters for fibroblast stress-related biological processes. Top GO terms when analysing the genes driving fibroblast clusters 2, 3 and 5.

Extended Data Fig. 4 Defining a catalogue of cell-population-enriched distal elements in fibroblasts, myeloid cells and endothelial cells using scATAC-seq.

a, Schematic highlighting the approach to integrate scRNA-seq data with scATAC-seq data12. See Supplementary Methods for details. b, Total scATAC-seq proximal and distal peaks identified in all cells. c, scATAC-seq t-SNE plot showing clusters and cell number of fibroblasts, myeloid cells and endothelial cells after integration with scRNA-seq data. d, Venn diagrams showing sample replicate convergence of cell-enriched distal elements found with scATAC-seq.

Extended Data Fig. 5 scATAC-seq defines chromatin accessibility in heart failure during intermittent exposure to BET bromodomain inhibition.

a, Chromatin accessibility at distal elements between samples in fibroblasts, myeloid cells and endothelial cells. Box plots show the 25th, 50th and 75th percentiles, with whiskers extending to the furthest value no further than 1.5× the interquartile range. The 10% most extreme points were trimmed for better visualization (these never included points within the whiskers of the box plot). Numbers above the box plots indicate significant P values, statistical significance (two-sided Wilcoxon rank-sum test) is shown for: sham versus TAC; sham versus TAC JQ1; TAC versus TAC JQ1 and TAC JQ1 versus TAC JQ1 withdrawn. b, Dynamic accessibility (mean and 95% confidence interval) of distal elements in fibroblasts (n = 4,394), myeloid cells (n = 1,325) and endothelial cells (n = 1,626) clustered by trend across samples. Accessibility trend and top GO terms (binomial test) associated with clusters 2, 6, 9, 11, 12 and 14 are shown for fibroblasts. For myeloid and endothelial cells, only the top GO terms (binomial test) associated with cluster 2 are shown. c, Enrichment scores for transcription-factor motif accessibility in distal elements between samples for the 10 most expressed transcription factors in TAC in fibroblasts, myeloid cells and endothelial cells. TF, transcription factor.

Extended Data Fig. 6 Nascent transcription in TGFβ-treated cells identifies stress-responsive distal and gene elements.

a, Schematic of the isolation and immortalization of mouse adult cardiac fibroblasts. b, Expression by qPCR of canonical markers of activated fibroblasts in unstimulated (Unstim) and TGFβ-treated cells. Unpaired, two-tailed Student’s t-test. c, Pearson correlation of the two independent biological replicates of PRO-seq in unstimulated and TGFβ-treated cells. d,e, Heat map of PRO-seq coverage of differentially transcribed distal regions (d) and protein-coding genes (e, right) between unstimulated and TGFβ-treated fibroblasts. Wald test with Benjamini–Hochberg correction. Signal for replicates 1 and 2 is shown. e, Right, top associated GO terms (Fisher’s exact test). f, PRO-seq tag density (±5 kb gene body) in unstimulated and TGFβ-treated cells in the genes differentially transcribed in unstimulated versus TGFβ-treated. Top, genes upregulated after TGFβ treatment. Bottom, genes downregulated after TGFβ treatment. g, PRO-seq tag density (±5 kb gene body) in unstimulated and TGFβ-treated cells in the set of genes upregulated (left, n = 260) or downregulated (right, n = 194) in TAC versus sham in fibroblasts in vivo. h, Co-accessibility (CoAc) change in fibroblasts of Postn peak 10/11 element with the promoters of genes within 1 Mb of the peak. Change in co-accessibility with the Postn promoter is highlighted in red. n = 27 genes within 1 Mb. Box plots show the 25th, 50th and 75th percentiles, with whiskers extending to the furthest value no further than 1.5× the interquartile range. i, Postn expression measured by qPCR in unstimulated and TGFβ-treated in the CRISPRi control line. Unpaired, two-tailed t-test. j, Postn peak 8, 10/11 and 19 eRNA expression measured by qPCR in unstimulated and TGFβ-treated fibroblasts in a CRISPRi control line and lines targeting peak 8, peak 10/11 or peak 19. Values are normalized to the CRISPRi control line in the unstimulated condition. One-way ANOVA followed by Sidak’s correction, statistical significance is shown between the unstimulated samples and TGFβ-treated samples. k, ChIP–qPCR data showing enrichment over chromatin input of H3K9me3 in control and Postn peak 10/11 CRISPRi lines in the unstimulated (left) and TGFβ-treated (right) condition. Regions amplifying peak 10, peak 11 and Postn promoters are shown. One-way ANOVA followed by Sidak’s correction, statistical significance is shown between control and Postn peak 10/11 CRISPRi lines. b, ik, Numbers above histograms show significant P values. Data are mean ± s.e.m.

Extended Data Fig. 7 Characterization of a catalogue of super-enhancers in fibroblasts, myeloid cells and endothelial cells.

a, Distribution of accessibility in fibroblasts, myeloid cells and endothelial cells in the TAC state identifies a class of distal regions (super-enhancers (SE)) for which the accessibility falls over the inflection point of the curve. b, c, Volcano plots showing correlation coefficients and corresponding P values (refer to the analysis depicted in Fig. 2e) of 239 super-enhancers in myeloid (b) and 267 super-enhancers in endothelial (c) cells. d, Distribution of H3K27ac in unstimulated and TGFβ-treated fibroblasts identifies a class of distal regions (super-enhancers) for which the accessibility falls over the inflection point of the curve. e, Fraction of H3K27ac in unstimulated and TGFβ-treated fibroblasts for the enhancers identified in vivo having a negative (left, n = 264) or positive (right, n = 206) correlation with heart function (based on analysis depicted in Fig. 2e). Box plots show the 25th, 50th and 75th percentiles, with whiskers extending to the furthest value no further than 1.5× the interquartile range.

Extended Data Fig. 8 Dynamic changes in chromatin accessibility at the Meox1 super-enhancer.

a, Comparison of left ventricle ejection fraction with chromatin accessibility at the Meox1 super-enhancer in fibroblasts, myeloid cells and endothelial cells. b, UMAP plot of Meox1 expression in all non-cardiomyocytes (n = 35,551). c, Chromatin accessibility at the Meox1 super-enhancer between samples in fibroblasts, myeloid cells and endothelial cells. Box plots show the 25th, 50th and 75th percentiles, with whiskers extending to the furthest value no further than 1.5× the interquartile range. Sample sizes (from left to right for each cell type): fibroblasts (n = 676, 979, 1,906, 1,654), myeloid cells (n = 631, 1,080, 1,021, 712), endothelial cells (n = 731, 1,666, 1,030, 851). Numbers above box plots show significant P values, statistical significance (two-sided Wilcoxon rank-sum test) is shown for: sham versus TAC, sham versus TAC JQ1, TAC versus TAC JQ1 and TAC JQ1 versus TAC JQ1 withdrawn. d, scATAC-seq average signal across cells in fibroblast samples at the Meox1 super-enhancer identifies multiple dynamic peaks in heart failure with pulsatile exposure to BET inhibition. e, Chromatin accessibility trend between samples (mean and 95% confidence interval) in all identified Meox1 super-enhancer peaks.

Extended Data Fig. 9 Brd4-dependent regulation of Meox1 expression.

a, Meox1 expression measured by qPCR in unstimulated and TGFβ-treated fibroblasts, treated with or without JQ1. b, Expression measured by qPCR of individual BET genes in unstimulated or TGFβ-treated fibroblasts treated with siRNA targeting control (siCtrl), Brd2 (siBrd2), Brd3 (siBrd3) or Brd4 (siBrd4). Statistical significance is shown between unstimulated samples and TGFβ-treated samples. c, Meox1 expression measured by qPCR in unstimulated or TGFβ-treated fibroblasts treated with siRNA targeting control, Brd2, Brd3 or Brd4. Statistical significance is shown between the TGFβ and control siRNA sample and the other TGFβ-treated samples. ac, All analysed samples were biological replicates. Numbers above graphs show significant P values (one-way ANOVA followed by Tukey post hoc test). Data are mean ± s.e.m.

Extended Data Fig. 10 The peak 9/10 Meox1 enhancer is strongly transcribed after TGFβ stimulation.

a, Volcano plot showing the log2[FC] of the PRO-seq signal of all identified distal scATAC-seq peaks in fibroblasts (n = 9,211) between unstimulated and TGFβ-treated fibroblasts. Meox1 peaks 9 (red) and 10 (orange) are highlighted. b, Co-accessibility change in fibroblasts of Meox1 peak 9/10 element with the promoters of genes within 1 Mb of the peak. Change in co-accessibility with the Meox1 promoter is highlighted in red. n = 115 genes within 1 Mb. Box plots show the 25th, 50th and 75th percentiles, with whiskers extending to the furthest value no further than 1.5× the interquartile range. c, d, Chromosome conformation capture (4C) using the Meox1 peak 9/10 region (c) or Meox1 promoter (d) as anchor point. 4C coverage in unstimulated and TGFβ-treated fibroblasts are shown in a 922-kb (top) and 328-kb (bottom) genomic regions. The last track represents the called TGFβ-induced loops with the anchor point (coloured in purple). e, Meox1 expression measured by qPCR in unstimulated and TGFβ-treated fibroblasts in the CRISPRi control line. Unpaired, two-tailed t-test. f, Meox1 peak 5, 9/10 and 13 eRNA expression measured by qPCR in unstimulated and TGFβ-treated fibroblasts in a CRISPRi control line and lines targeting peak 5, peak 9/10 or peak 13. Values are normalized to the CRISPRi control line in the unstimulated condition. One-way ANOVA followed by Sidak’s correction, statistical significance is shown between unstimulated samples and TGFβ-treated samples. g, ChIP–qPCR data showing enrichment over chromatin input of H3K9me3 in control and Meox1 peak 9/10 CRISPRi lines in the unstimulated (left) and TGFβ-treated (right) conditions. Regions amplifying peak 9, peak 10 and Meox1 promoters are shown. One-way ANOVA followed by Sidak’s correction, statistical significance is shown between CRISPRi control and targeted lines. h, Droplet digital (dd)PCR amplifying a wild-type or mutated region of Meox1 peak 9/10 DNA. Parental fibroblast cell line, wild type (clone 20, isogenic control exposed to CRISPR Cas9 and gRNAs) and peak 9/10 knockout (KO) (clone 16) cell lines are shown. i, Schematic showing the Meox1 locus with the scATAC-seq average signal across fibroblasts in TAC. SMAD2/3 motifs (Jaspar, MA1622.1) in the peak 9/10 region and in the Meox1 promoter (±1 kb from the transcription start site (TSS)) are highlighted. j. Expression measured by qPCR of Smad2 (left) and Smad3 (right) in unstimulated or TGFβ-treated fibroblasts with siRNA targeting control and Smad2 (left) or Smad3 (right). One-way ANOVA followed by Tukey post hoc test. k, Meox1 expression measured by qPCR in unstimulated or TGFβ-treated fibroblasts with siRNA targeting either control or Smad2. One-way ANOVA followed by Tukey post hoc test. eg, j, k, Numbers above histograms show significant P values. Data are mean ± s.e.m.

Extended Data Fig. 11 MEOX1 is a regulator of fibroblast activation.

a, b, Meox1 expression measured by qPCR in mouse primary cardiac fibroblasts (a) and immortalized cardiac fibroblasts (b) in the unstimulated condition, or after treatment with TGFβ and control siRNA or TGFβ and Meox1 siRNA. One-way ANOVA followed by Tukey post hoc test. c, Left, immunofluorescence staining of αSMA in unstimulated and TGFβ-treated cells treated with a control or a Meox1-targeting siRNA. Nuclei are marked by Hoechst. Scale bars, 100 μm. Right, quantification of αSMA staining (two independent experiments). The fold change in intensity is normalized to the cell number. One-way ANOVA followed by Tukey post hoc test. d, Expression of Acta2 (which encodes αSMA) measured by qPCR in the unstimulated condition, or after treatment with TGFβ and control siRNA or TGFβ and Meox1 siRNA. One-way ANOVA followed by Tukey post hoc test. e, Left, representative images of EdU incorporation in the unstimulated condition, or after treatment with TGFβ and control siRNA or TGFβ and Meox1 siRNA. DAPI (blue), EdU (red) and CellMask (green). Scale bars, 200 μm. Right, quantification (two independent experiments). One-way ANOVA followed by Tukey post hoc test. f, Meox1 expression measured by qPCR in wild-type and Meox1 overexpression (o/e) mouse immortalized cardiac fibroblasts. Unpaired, two-tailed t-test. g, Pearson correlation of the three replicates of MEOX1 anti-haemagglutinin (HA) ChIP–seq in unstimulated and TGFβ-treated cells. h, MEOX1 anti-HA ChIP–seq coverage in all protein-coding genes (±2 kb gene body) in unstimulated and TGFβ-treated fibroblasts. i, Pearson correlation of the two independent biological replicates of PRO-seq for TGFβ and control siRNA or TGFβ and Meox1 siRNA treatments. j, PRO-seq coverage in the unstimulated condition, and after treatment with TGFβ and control siRNA or TGFβ and Meox1 siRNA at the distal elements defined as more transcribed in TGFβ versus unstimulated (2,101 sites) (see Fig. 2a) that are either bound by MEOX1 (496 regions, top) or not (1,605 regions, bottom). k, PRO-seq coverage in the unstimulated condition, or after treatment with TGFβ and control siRNA or TGFβ and Meox1 siRNA at the distal elements with high H3K27ac enrichment in the unstimulated condition bound by MEOX1 (379 regions). l, PRO-seq coverage of differentially transcribed genes (Wald test followed by Benjamini–Hochberg correction) in TGFβ-treated fibroblasts with control or Meox1 siRNA. Signal for replicates 1 and 2 is shown. m, PRO-seq tag density (±5 kb gene body) after treatment with TGFβ and control siRNA or TGFβ and Meox1 siRNA in genes upregulated in TGFβ and control siRNA versus TGFβ and Meox1 siRNA (left); and genes upregulated in TGFβ and Meox1 siRNA versus TGFβ and control siRNA (right). n, Violin plot showing the normalized expression scores of genes upregulated in TGFβ and control siRNA versus TGFβ and Meox1 siRNA in PRO-seq that were captured in the scRNA-seq data. Expression of sham and TAC fibroblast samples is shown. o, Number of MEOX1-bound genes in MEOX1 ChIP–seq (in TGFβ-treated cells) in ±2 kb gene body, ±100 kb gene body or ±500 kb gene body in genes differentially transcribed in PRO-seq: upregulated in TGFβ versus unstimulated (left); downregulated in TGFβ versus unstimulated (centre left); upregulated in TGFβ and control siRNA versus TGFβ and Meox1 siRNA (centre right); upregulated in TGFβ and Meox1 siRNA versus TGFβ and control siRNA (right). p, Coverage of MEOX1 ChIP (TGFβ-treated cells), H3K27ac ChIP–seq (unstimulated and TGFβ-treated cells) and PRO-seq (unstimulated condition, or treatment with TGFβ and control siRNA or TGFβ and Meox1 siRNA) at the Postn locus. The Postn peak 10/11 region is highlighted in red. af, Numbers above graphs show significant P values. Data are means ± s.e.m.

Extended Data Fig. 12 MEOX1 is expressed in human activated fibroblasts.

a, POSTN (left) and MEOX1 (right) expression in human adult fibroblast clusters. y axes, normalized UMI levels20. b, Track showing scATAC-seq average signal across fibroblasts in the human fetal heart21 in the MEOX1 locus. The syntenic region of peak 9/10 is highlighted in red. c, Bulk RNA-seq data of human MEOX1 expression (fragments per kilobase of transcript per million mapped reads, FPKM) in heart tissue in control individuals (Ctrl) and individuals with dilated cardiomyopathy (DCM) or hypertrophic cardiomyopathy (HCM) (GSE141910). Unpaired, two-tailed t-test with Benjamini–Hochberg correction. d, Bulk RNA-seq data of human MEOX1 expression (raw counts) in lung tissue between control individuals and individuals with idiopathic pulmonary fibrosis (IPF) (GSE134692)22. Unpaired, two-tailed t-test. c, d, Numbers above the graphs show significant P values.

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Alexanian, M., Przytycki, P.F., Micheletti, R. et al. A transcriptional switch governs fibroblast activation in heart disease. Nature 595, 438–443 (2021). https://doi.org/10.1038/s41586-021-03674-1

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