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Niche stiffening compromises hair follicle stem cell potential during ageing by reducing bivalent promoter accessibility

Nature Cell Biology volume 23, pages 771–781 (2021)Cite this article

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Abstract

Tissue turnover requires activation and lineage commitment of tissue-resident stem cells (SCs). These processes are impacted by ageing, but the mechanisms remain unclear. Here, we addressed the mechanisms of ageing in murine hair follicle SCs (HFSCs) and observed a widespread reduction in chromatin accessibility in aged HFSCs, particularly at key self-renewal and differentiation genes, characterized by bivalent promoters occupied by active and repressive chromatin marks. Consistent with this, aged HFSCs showed reduced ability to activate bivalent genes for efficient self-renewal and differentiation. These defects were niche dependent as the transplantation of aged HFSCs into young recipients or synthetic niches restored SC functions. Mechanistically, the aged HFSC niche displayed widespread alterations in extracellular matrix composition and mechanics, resulting in mechanical stress and concomitant transcriptional repression to silence promoters. As a consequence, increasing basement membrane stiffness recapitulated age-related SC changes. These data identify niche mechanics as a central regulator of chromatin state, which, when altered, leads to age-dependent SC exhaustion.

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Fig. 1: Age-induced HFSC exhaustion is associated with decreased chromatin accessibility.
Fig. 2: HFSC ageing results in the silencing of bivalent promoters.
Fig. 3: Ageing leads to niche-dependent compromised activation of bivalent genes and loss of SC potential.
Fig. 4: Widespread biochemical alterations in the ECM induce niche stiffening to control SC potential.
Fig. 5: Increased BM stiffness compromises HFSC maintenance in vivo.
Fig. 6: Mechanical stress suppresses transcription to silence bivalent promoters.

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Data availability

Sequencing data that support the findings of this study have been deposited at the Gene Expression Omnibus (GEO) under the accession code GSE148619. Proteomics data have been deposited to the ProteomeXchange Consortium through the PRIDE partner repository51 under the dataset identifier PXD018352. Previously published sequencing data14 that were reanalysed here are available under the accession code GSE31239. Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank A. M. Luoto and N. Hachenberg for expert technical assistance; A. Gyenis for help with experiments; M. Loparic and D. Schneider for initial atomic force microscopy measurements; L. Sorokin for laminin antibodies; the staff at the FACS & Imaging Facility of MPI for Biology of Ageing, the Imaging Facility of CECAD Cologne and the Biomedicum Helsinki Imaging Unit for imaging support; and C. Becker and E. Kirstat at the Cologne Center for Genomics for help with sequencing. This work was supported by the Sigrid Juselius Foundation, Helsinki Institute of Life Science, Wihuri Research Institute, Max Planck Society, the Max Planck Förderstiftung and the European Research Council (ERC) under the EU Horizon 2020 research and innovation programme (grant agreement 770877—STEMpop) (all to S.A.W.) and the Deutsche Forschungsgemeinschaft (DFG; project number 73111208—SFB 829 (to S.A.W., C.M.N. and A.R.-I.), and FOR2722 to M.K. Y.A.M. is the recipient of the EMBO Long-Term fellowship ALTF 728-2017 and Human Frontier Science Program fellowship LT000861/2018.

Author information

Authors and Affiliations

  1. Max Planck Institute for Biology of Ageing, Cologne, Germany

    Janis Koester, Yekaterina A. Miroshnikova, Sushmita Ghatak, Carlos Andrés Chacón-Martínez, Jessica Morgner, Xinping Li, Ilian Atanassov & Sara A. Wickström

  2. Cologne Excellence Cluster for Stress Responses in Ageing-associated diseases (CECAD), University of Cologne, Cologne, Germany

    Janis Koester, Yekaterina A. Miroshnikova, Carien M. Niessen, Alvaro Rada-Iglesias & Sara A. Wickström

  3. Helsinki Institute of Life Science, Biomedicum Helsinki, University of Helsinki, Helsinki, Finland

    Yekaterina A. Miroshnikova & Sara A. Wickström

  4. Wihuri Research Institute, Biomedicum Helsinki, University of Helsinki, Helsinki, Finland

    Yekaterina A. Miroshnikova & Sara A. Wickström

  5. Stem Cells and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland

    Yekaterina A. Miroshnikova & Sara A. Wickström

  6. Cologne Center for Genomics, University of Cologne, Cologne, Germany

    Janine Altmüller

  7. Department of Molecular Pharmacology & Physiology, University of South Florida, Morsani College of Medicine, Tampa, FL, USA

    David E. Birk

  8. Institute for Dental Research and Oral Musculoskeletal Research, Center for Biochemistry, University of Cologne, Cologne, Germany

    Manuel Koch

  9. Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany

    Manuel Koch, Michaela Bartusel, Carien M. Niessen & Alvaro Rada-Iglesias

  10. Molecular and Cellular Sport Medicine, German Sport University Cologne, Cologne, Germany

    Wilhelm Bloch

  11. Department of Dermatology, Center for Molecular Medicine, University of Cologne, Cologne, Germany

    Carien M. Niessen

  12. Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), University of Cantabria/CSIC, Cantabria, Spain

    Alvaro Rada-Iglesias

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  1. Janis Koester
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Contributions

J.K. designed and performed most of the experiments and analysed data. Y.A.M. performed atomic force microscopy, immunostainings, organoid experiments, designed experiments and analysed data. S.G. performed the HFSC quantification and BrdU feeding experiments. C.A.C.-M. performed cell sorting and depilation experiments with J.K. J.M. performed immunostainings. X.L. and I.A. performed proteomics experiments. W.B. performed electron microscopy. J.A. performed ChIP sequencing. D.E.B. and M.K. provided collagen XIV and Tnx mutant mice and other key reagents. M.B. and A.R.-I. supported the ATAC-seq experiments and analysis of sequencing data. C.M.N. and A.R.-I. designed experiments and analysed data. S.A.W. conceived and supervised the study, designed experiments, analysed data and wrote the paper. All of the authors commented and edited the manuscript.

Corresponding author

Correspondence to Sara A. Wickström.

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The authors declare no competing interests.

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Peer review information Nature Cell Biology thanks Karl Lenhard Rudolph 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 Analyses of young and aged HFSCs using flow cytometry, ATACseq and RNAseq.

a, Representative images of young (6 month) and aged (24 month) old mice show no visible differences in haircoats. (b,c) Immunofluorescence imaging (b) and quantification (c) of hair follicle density from young and old mice (mean ±SD; n = 5 mice/group). Scale bars 100 µm. d, Quantification of CD34 + /α6 integrin+ HFSCs by flow cytometry from young and aged mice cohorts from two different animal facilities (facilities #2 and #3, facility #1 shown in main Fig. 1b), where the respective young and aged mice were housed in the same room. Note decreased HFSC levels in mice from both facilities (mean, n = 7 mice/group; *p = 0.0293 Student’s t-test (facility #2), n = 4 mice/group; *p = 0.0283, Mann-Whitney (facility #3)). e, Plotting relative abundance of CD34 + HFSCs as a function of anagen-to-telogen ratio shows no correlation between the two parameters in young or aged mice (n = 15 young/14 aged mice; R2 = 0.0001168, Pearson’s correlation). f, Fragment frequency distribution of the ATACseq reads shows expected distribution both in young and aged biological replicates (n = 4 mice/group). g, Motif enrichment analyses of differentially accessible ATACseq peaks shows enrichment of CpG islands and promoter regions in regions more accessible in young HFSCs, whereas more accessible peaks in aged HFSCs are enriched in transposable elements. (-log(p) values: CpG islands – yHFSCs: 670.48/ aHFSCs: 2.03; promoters - yHFSCs: 289.13, aHFSCs: 1.22; 5’ utr - yHFSCs: 203.36, aHFSCs: 2.69; IAPEz-int|LTR | ERVK - young HFSCs: -40.18, aged HFSCs: 83.66; LTR | ERVK - young HFSCs: -151.31, aged HFSCs: 12.56) (h) Volcano plot of significantly altered transcripts in young and aged HFSCs. Genes involved in differentiation (eg. Mef2c, Gata6, Sox21, Tcf24), proliferation and signaling (Ptch1, Fgfr2, Tgfa, Nptx1), actin cytoskeleton (Espn, Fhod3, Smoc2), and stemness (Peg3) are among the most regulated (n = 3 mice/group; padj<0.05, Wald test/Benjamini-Hochberg). (i) GO-term analyses of genes up- and down-regulated in aged HFSCs.

Source data

Extended Data Fig. 2 Histone methylation analyses of young and aged HFSCs.

a, Heatmap of differentially accessible intergenic regions clustered according to H3K4me1, H3K27ac, H3K27me3 as well as the transcripts of these regions quantified by RNAseq from young and aged HFSCs. Note that most regions have high H3K4me1, but low H3K27ac and no detectible transcripts, indicative of a primed enhancer state. b, GO term analyses of the regions in (a) implicate enhancers for genes involved processes such as cell-cell adhesion, tissue development, cell differentiation, and proliferation to be less accessible (upper panel), whereas enhancers for genes involved in actin cytoskeleton organization and regulation of cell adhesion are more accessible (lower panel) in aged HFSCs. c, Heatmap of H3K27me3 ChIP sequencing peaks from young (H3K27me3-Y) and aged (H3K27me3-A) HFSCs shows slightly increased peak intensity in aged HFSCs (n = 2 mice/group). d, Box plot of -log2 fold changes of H3K4me3 occupancy at promoters of aged HFSC compared to young (top, middle and bottom delimiters are the 75th, 50th, 25th percentiles; top and bottom whiskers are the 90th and 10th percentiles; n = 2 mice/group). e, Representative genes from cluster-4 with functions in stem cell (SC) fate, differentiation and self-renewal include key genes required for HFSC activation and differentiation.

Source data

Extended Data Fig. 3 Niche-dependent regulation of HFSC potency and epigenetic state.

a, Representative images and quantification of BrdU incorporation in bulge (Bu) HFSCs from mice fed with BrdU in drinking water for 4 weeks. Note reduced BrdU incorporation in aged HFSCs (n = 3 mice/group). Scale bars 25 µm. b, Quantitative RT-PCR of RNAi knockdowns for selected genes with bivalent promoter state (n = 3 independent experiments). (c-e) Representative images (c) and quantification of colony number (d) and size (e) from colony forming assays with HFSCs depleted of the indicated genes (n = 3 independent experiments; *p = 0.0263, RM-ANOVA/Fischer’s, **p = 0.0045, Friedman/Dunn’s). f, Representative images and quantification of H3K4me3 in hair follicles generated in young nude mice by transplanting young or aged HFSCs (n = 3 mice/group). Scale bars 25 µm. g, Quantitative RT-PCR of selected genes with bivalent promoter state and reduced accessibility in vivo from H3K4me3 ChIP of young and aged HFSCs in 24 h 3 C organoid cultures. No significant differences in expression are observed (n = 4 mice/group). h, Quantitative RT-PCR of selected genes with bivalent promoter state and reduced accessibility in vivo from young and aged HFSCs in 3 C organoid cultures. No significant differences in expression are observed (n = 4 mice/group). Bar graphs in g, h show mean ±SEM, others mean ±SD.

Source data

Extended Data Fig. 4 Basement membranes in young and aged skin and decellularized scaffolds.

a, Representative immunofluorescence images and quantification of Laminin 332 staining show increased levels in aged BMs (mean; n = 4 mice/group, *p = 0.0286, Mann-Whitney; Scale bars 50 µm). b, Representative immunofluorescence images and quantification of Laminin 511 staining show increased levels in aged BMs (mean; n = 4 mice/group, *p = 0.0286, Mann-Whitney; Scale bars 50 µm). c, Schematic illustration of decellularized basement membrane scaffold preparation from young and aged mice. d, Immunofluorescence images of decellularized basement membrane scaffolds showing absence of epidermal cell nuclei but intact basement membranes as marked by Collagen IV and Laminin 332 staining. A representative of 3 mice is shown. Scale bars 100 µm. e, Box and whiskers plot of atomic force microscopy force indentation measurements of 3 C organoid hydrogel stiffness (top, middle and bottom delimiters are the 75th, 50th, 25th percentiles; top and bottom whiskers are the maximum and minimum; n = 13 force curves pooled across 4 independent experiments; **p = 0.0012, Kolmogorov-Smirnov).

Source data

Extended Data Fig. 5 Analyses of Collagen-XIV- and Tenascin-X-deficient mice.

a, Hematoxylin/Eosin stainings from 1 year old Collagen-XIV-deficient (Col XIV -/-) and wild type (ColXIV + /+) control mice reveal no overt skin pathology. Scale bars 100 µm. Representative images from 3 mice/genotype are shown. b, Immunofluorescence images of Cd34 staining to mark the bulge (bu) niche from 1 year old Col XIV + / + and -/- mice show comparable hair follicle morphology. Representative images from 3 mice/genotype are shown. Scale bars 25 µm. c, Quantification of CD34 + /α6 integrin+ HFSCs by flow cytometry from 6 months old Col XIV + / + and -/- mice shows no major reduction in levels of HFSCs (n = 5 Col XIV + / + and n = 4 Col XIV -/- mice). d, Quantification of basement membrane (BM) thickness from skin electron micrographs of Tenascin-X-deficient (TnX -/-) and wild type (TnX + /+) control mice. Note increased BM thickness in TnX -/- mice (n = 4 mice/group; *p = 0.0286, Mann-Whitney). e, mHematoxylin/Eosin stainings from 1 year old TnX + /+ and TnX -/- mice show no overt skin pathology. Representative images from 3 mice/genotype are shown. Scale bars 100 µm. f, Immunofluorescence images of Keratin-15 staining to mark the bulge (bu) niche from 1 year old TnX + /+ and -/- mice show comparable hair follicle morphology. Representative images from 3 mice/genotype are shown. Scale bars 25 µm. g, Quantification of CD34 + /α6 integrin+ HFSCs by flow cytometry from 6 months old TnX + /+ and -/- mice shows slightly reduced levels of HFSCs in TnX -/- mice (n = 7 TnX + /+ and n = 8 TnX -/- mice; *p = 0.0301, Student’s t-test). Bar graphs show mean ±SD.

Source data

Extended Data Fig. 6 Analyses of contractility and transcription in hair follicles and organoid cultures.

a, Representative immunofluorescence images and quantification of phosphorylated myosin light chain 2 (pMLC2). Note increased pMLC2 indicating increased contractility in aged bulge (bu) HFSCs (n = 5 young and n = 4 aged mice; *p = 0.0451, Student’s t-test; Scale bar 50 µm). b, Quantification of the nuclear aspect ratio (major axis/minor axis) shows increased nuclear elongation of aged HFSCs (n = 5 mice/group with >100 nuclei per mouse; **p = 0.0031, Student’s t-test). c, Representative images and quantification of H3K4me3 intensity from HFSC organoids treated with Kdm5 inhibitor (Kdm5i) (n = 6 independent experiments; p = 0.0515, Student’s t-test; Scale bar 50 µm). d, Quantitative RT-PCR of selected genes with bivalent promoter state from HFSC organoids treated with Kdm5i (n = 4 independent experiments). Bar graphs show mean ±SD.

Source data

Supplementary information

Supplementary Information

Supplementary Fig. 1: the gating strategy for quantification and purification of integrin α6+CD34+ HFSCs by FACS.

Reporting Summary

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Supplementary Tables 1–7

Supplementary Table 1: differential peak analysis of ATAC-seq data. Analysis of differentially accessible genomic regions in young and aged HFSCs using ATAC-seq. Supplementary Table 2: differential gene expression analysis of RNA-seq data. Analysis of differentially expressed genes in young and aged HFSCs using RNA-seq. Supplementary Table 3: differential peak analysis of H3K4me3 ChIP–seq data. Analysis of differential H3K4me3 peaks in young and aged HFSCs. Supplementary Table 4: differential peak analysis of H3K27me3 ChIP–seq data. Analysis of differential H3K27me3 peaks in young and aged HFSCs. Supplementary Table 5: differential protein abundance analysis of proteomics data. Analyses of differences in proteome in young and aged skin. Supplementary Table 6: differential peak analysis of RNAPII ChIP–seq data. Analysis of differential RNAPII peaks in young and aged HFSCs. Supplementary Table 7: primers used in this study. A list of primers used for ChIP PCR and PCR in this study.

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Koester, J., Miroshnikova, Y.A., Ghatak, S. et al. Niche stiffening compromises hair follicle stem cell potential during ageing by reducing bivalent promoter accessibility. Nat Cell Biol 23, 771–781 (2021). https://doi.org/10.1038/s41556-021-00705-x

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