Abstract
Although most acute skin wounds heal rapidly, non-healing skin ulcers represent an increasing and substantial unmet medical need that urgently requires effective therapeutics. Keratinocytes resurface wounds to re-establish the epidermal barrier by transitioning to an activated, migratory state, but this ability is lost in dysfunctional chronic wounds. Small-molecule regulators of keratinocyte plasticity with the potential to reverse keratinocyte malfunction in situ could offer a novel therapeutic approach in skin wound healing. Utilizing high-throughput phenotypic screening of primary keratinocytes, we identify such small molecules, including bromodomain and extra-terminal domain (BET) protein family inhibitors (BETi). BETi induce a sustained activated, migratory state in keratinocytes in vitro, increase activation markers in human epidermis ex vivo and enhance skin wound healing in vivo. Our findings suggest potential clinical utility of BETi in promoting keratinocyte re-epithelialization of skin wounds. Importantly, this novel property of BETi is exclusively observed after transient low-dose exposure, revealing new potential for this compound class.
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Data availability
Refined coordinates for the crystal structure data shown in Fig. 1b have been deposited in the PDB database with identification code 6ZCI. BRD4 ChIP-seq data shown in Fig. 3 and Extended Data Figs. 6 and 7 have been deposited to the NCBI GEO database under accession no. GSE130365. BRD4 ChIP-seq peaks shown in Fig. 3a,c, as well as in Extended Data Figs. 6b and 7b, were annotated using the ChromHMM (http://compbio.mit.edu/ChromHMM/) chromatin state profile of normal human epidermal keratinocytes from ENCODE (https://www.encodeproject.org/). H3K27ac ChIP-seq data from untreated, low-passage human primary epidermal keratinocytes, as shown in Fig. 3c and Extended Data Fig. 7b, were taken from ref. 29. RNA-seq data have not been deposited to a public repository to protect the donor confidentiality of commercially available primary human keratinocytes. Instead, the following are available. The gene-based count table for RNA-seq data shown in Extended Data Fig. 4 is included as Supplementary Data 2 text file ‘Schutzius_Dataset_2.txt’. The gene-based count table for RNA-seq data shown in Fig. 4a and Extended Data Fig. 8 is included as Supplementary Data 3 text file ‘Schutzius_Dataset_3.txt’. The gene-based count table for RNA-seq data shown in Fig. 4b is included as Supplementary Data 4 text file ‘Schutzius_Dataset_4.txt’. Gene set enrichment analysis based on RNA-seq data as shown in Extended Figs. 7c and 8 was performed using the Molecular Signatures Database (MSigDB, v7.0, https://www.gsea-msigdb.org/gsea/msigdb/). The ATAC-seq data shown in Extended Data Fig. 9 were deposited in the NCBI GEO database under accession no. GSE134306. Source data are provided with this paper.
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Acknowledgements
We thank P. Mistry for discussion of the BET bromodomain inhibitors, L. Leder for involucrin protein preparation, J. Richter for help with keratinocyte migration assay development, J. Knehr for sequencing, M. Patoor and M. Livendahl for compound synthesis and analysis, J. Nagel for quantitative mass spectrometry, G. Hintzen and N. Carballido for help with preparation of split skin, S. Ley for help with histology and A. Sonrel, F. Kiefer and N. Renaud for implementing the chromatin analysis pipeline used in this study. We are grateful to J. Bradner for discussions.
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Contributions
S.K. conceptualized the study. G.S. conceptualized the primary screening assay and keratinocyte migration assays and generated the data. G.S., along with A.S., A.A. and S.K., generated keratinocyte assay data. F.F., S.R., F.N., F.G. and L.B. performed compound selection and generated and analyzed data from the HTS. J.L., C.D. and L.J.J. generated FACS data. V.G., H.R., P.W.M., S.C., A.V. and R. Tiedt identified and developed proprietary BETi scaffolds. J.B. and P.D. generated bromodomain selectivity data. F.L., C.K. and S.K. conceptualized, designed and interpreted all keratinocyte-based molecular profiling (RNA, ChIP and ATAC) studies. G.S. and A.S. performed RNA-seq profiling, F.L. and J.T. performed ChIP-seq and ATAC-seq profiling of keratinocytes. W.C. performed sequencing. C.K. and S.B. performed ChIP-seq analysis, and C.K. performed RNA-seq and ATAC-seq analysis of keratinocyte experiments. S.M.R. performed RNA-seq analysis of patient samples. C.G.K. and G.R. supervised all molecular profiling (RNA, ChIP and ATAC) analysis and interpretation. J.R.T., D.B. and M.S. performed chemical proteomics and mass spectrometry. L.B. designed and synthesized linker compounds for chemical proteomics. M. Frederiksen provided compounds and advice. N.L. provided compound analysis. M. Faller, J.K., R.H. and F.Z. generated crystal structures. N.D. synthesized NVS-BET-2. A. Beyerbach and A.Z. performed pharmacokinetics analysis. A.R. identified the in vivo study formulation. F.T., along with M.L. and V.G., generated mouse in vivo data. F.T., A.R., S.S., A.B., N.D. and S.K. interpreted mouse in vivo data. H.R. generated chronic wound sample data. A. Berwick provided project management. P.T. provided mentorship to the team. V.D. provided clinical advice to the team. T.B., N.D., M.F., C.K., H.R., C.G.K, G.R., V.D., R. Terranova, G.S., M. Frederiksen, F.L. and S.K. wrote the manuscript.
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Extended data
Extended Data Fig. 1 Discovery of small molecule regulators of keratinocyte stem cell fate.
(a,b) Screening concept using calcium driven differentiation combined with TR-FRET assay for differentiation marker involucrin. The TR-FRET assay was optimized in pilot experiments in 384-well format and then miniaturized for the primary screen to 1536-well format with a Z’ mean 0.66 ± 0.18 over plates. (c) Screening flow chart starting with 108,000 compounds followed by several triaging selections leading to a final 110 active compounds. (d) HTS screen showing involucrin expression in the presence of all compounds tested at 1.25 µM (threshold for further validation was >30% reduction in involucrin expression). (e) Inhibition of involucrin (TR-FRET) expression versus cell number for 625 compounds in dose response. Compounds with >30% reduction in involucrin expression and <45% reduction in cell number at 10 µM were selected for further follow-up. Compound MoA annotation for most potent hit classes identified are shown: BET bromodomain inhibitor (red), Gamma secretase inhibitor (blue) or HDAC inhibitor (yellow). (f) 158 selected compounds (IC50 < 10 µM and <60% reduction in cell number at 10 µM in neonatal keratinocytes) validated in dose response on adult keratinocytes, correlating IC50 values (inhibition of involucrin expression) on adult versus neonatal cells. The middle gray line is the line of equality, where both IC50 values are identical, and the gray-dashed lines are one log unit above and below the line of equality (quisinostat; JQ1; I-BET151; I-BET762; DAPT). Color coding as in (e) with representative compounds per hit class labeled.
Extended Data Fig. 2 HDAC inhibitors, Gamma-secretase inhibitors and BET bromodomain inhibitors block human keratinocyte differentiation.
(a) TR-FRET measurement of involucrin protein levels in human neonatal keratinocytes in the presence of increasing concentrations of Quisinostat (HDAC inhibitor), MK-0752 (Gamma secretase inhibitor; GSI), JQ1 (BET bromodomain inhibitor) and (b) TR-FRET for involucrin in human neonatal keratinocytes after 24 h treatment with 1.2 mM CaCl2 in the presence of either 10 or 1 µM JQ1 or its inactive enantiomer JQ1(-), I-BET762 or its inactive enantiomer I-BET762(-), I-BET151, Vorinostat (HDAC inhibitor), or MK-0752 (GSI) (mean ± s.d., n = 3) (c) Involucrin protein expression by Western blot in adult keratinocytes in the presence of 1 µM Vorinostat, 1 µM MK-0752 (GSI), 0.5 µM JQ1 (BETi) or 0.5 µM JQ1(-) (n = 2) (d) TR-FRET measurement of involucrin in neonatal keratinocytes after 24 h of treatment with 1.2 mM CaCl2 in the presence of EGF (100 ng/ml), HGF (100 ng/ml), HB-EGF (100 ng/ml) or ROCK-Inhibitor (Y-27632; 10 µM) (Mean ± S.D. n = 4, Two-way ANOVA with Sidak’s multiple comparisons test: ****p < 0.0001).
Extended Data Fig. 3 DiscoverX BROMOscan selectivity screens.
TREESpot rendering of binding affinity for NVS-BET-1 and NVS-BET-2 screened at 1 µM concentration across a panel of 32 bromodomains indicated in black on the human bromodomain phylogenetic tree dendrogram. Bromodomain-containing proteins not part of panel shown in gray. Size of circle represents ligand binding affinity per given target expressed as percent control (DMSO = 100%), see Supplementary Dataset 1.
Extended Data Fig. 4 Keratinocyte global gene expression profiles after exposure to JQ1 and NVS-BET-1 are highly correlated.
Differential expression analysis on RNA-seq data was performed on the counts per million (CPMs) using a limma voom workflow with abs(log2FC) > 1 & adjusted p-value < 0.01. Correlation of changes in global gene expression (by RNA-seq) of human keratinocytes after 8 h incubation with either 125 nM JQ1 or 125 nM NVS-BET-1, plotting log2 fold-changes in expression between BETi- versus DMSO-treated cells as indicated. Dotted red lines indicate significance cut-offs, with regression line in black and a correlation coefficient of R2 = 0.95. Previously published markers of BETi target engagement shown as upregulated (HIST2H2BE, SERPINI1, HEXIM1, CLU) or downregulated (MYC, ZMYND8, MCM5 and IL7R).
Extended Data Fig. 5 BET bromodomain inhibitors increase human keratinocyte migration.
Primary adult human keratinocyte migration assay (a) Following ‘wounding’ of a confluent monolayer of keratinocytes, growth factors IGF-1, HB-EGF and HGF (10 ng/ml) were added and migration of cells into the wounded area monitored over time by imaging (mean ± s.d. n = 3, Two-way ANOVA with Dunnett’s correction for multiple comparison: IGF-1: *p = 0.0435, ***p = 0.0008, ****p < 0.0001, HGF: ###p = 0.002, ####p < 0.0001, and HB-EGF: ##p = 0.0015, ####p < 0.0001. (b) Overnight pretreatment and removal of BET inhibitor NVS-BET-2 at time 0 and migration of cells into the wounded area monitored over time by imaging (mean ± s.d. n = 8 ctrl and n = 6 treated, Two-way ANOVA with Sidak’s multiple comparisons test: ****p < 0.0001) (c) Keratinocytes were incubated for 8 h in 500 nM or 1.5 µM JQ1, NVS-BET-1 or NVS-BET-2, followed by compound removal and incubation for a further 18 h before live-cell surface staining for ITGA6, CD44 and ITGA3 using FACS analysis. Two-way ANOVA with Dunnett’s multiple comparisons test (mean ± s.d. n = 3). ITGA6 (JQ1, 500 nM p = 0.0017**, 1.5 µM p = 0.0039**. NVS-BET-1 500 nM p = 0.0007***, 1.5 µM p = 0.0045** NVS-BET-2 500 nM p = 0.0048**, 1.5 µM p = 0.0009***) CD44 (JQ1 500 nM p = 0.0019**, 1.5 µM p = 0.0008*** NVS-BET-1 500 nM p = 0.0002***, 1.5 µM p < 0.0001*** NVS-BET-2 500 nM p = 0.0016**, 1.5 µM p = 0.0012** ITGA3 (JQ1 500 nM p = 0.0003***, 1.5 µM p = 0.0003*** NVS-BET-1 500 nM p = 0.0064**, 1.5 µM p = 0.0034** NVS-BET-2 500 nM p = 0.0033**, 1.5 µM p = 0.0041**). (d) Keratinocytes were incubated for 12 h with either NVS-BET-1 or NVS-BET-2 at multiple concentrations, followed by compound removal and incubation for a further 96 h without compounds. Cell number was estimated using metabolic reagent WST-1 (Abs). Values expressed as percentage control (mean ± s.d. n = 12. Two-way RM ANOVA with Dunnett’s multiple comparisons test: *p = 0.0227 (NVS-BET-1) and *p = 0.0415 (NVS-BET-2), **p = 0.0018 (NVS-BET-1) and, ****p < 0.0001). The box extends from the 25th to 75th percentiles, center line shows median, and whiskers representing minimal and maximal value.
Extended Data Fig. 6 BRD4 occupancy in response to treatment with NVS-BET-1 is highly dynamic.
(a) Spearman correlation of BRD4 peaks genome-wide in human keratinocytes after treatments as indicated, averaged across replicates per condition. (b) Normalized BRD4 ChIP-seq signal centered on peak summit (± 1.5 kb) at genomic loci that displayed significant change in occupancy signal in response to 125 nM NVS-BET-1 compared to DMSO control at 6 h (Differential analysis was performed using DiffBind with DESeq2 (abs(log2FC) > 1 & p-value < 0.01). Peaks are clustered by direction of fold-change (occupancy ‘Down’ versus ‘Up’, as labeled in side heat map on right) and ranked by signal strength with functional annotation based on NHEK ChromHMM signal.
Extended Data Fig. 7 BRD4 chromatin occupancy displays differential BETi sensitivity at super-enhancer versus promoter regions.
(a) Ranking of enhancers (pink) by BRD4 signal versus signal at a given enhancer based on BRD4 ChIP-seq in keratinocytes per condition as indicated identifies super-enhancers (blue). (b) Genome browser track view of BRD4 occupancy (ChIP-seq signal) at HIST2H2BE genomic locus upon treatment conditions as indicated. Chromosome coordinates as well as super-enhancer and promoter locations labeled, with H3K27ac ChIP-seq data taken from low-passage untreated HPEK and ChromHMM taken from ENCODE NHEK. (c) MSigDB gene set enrichment analysis of genes associated based on proximity with BRD4 ChIP-seq peaks found to be significantly upregulated at 6 h with 125 nM NVS-BET-1 compared to DMSO as shown in Fig. 4b. (d) CpG content analysis of top 100 down- or upregulated BRD4 ChIP-seq peaks overlapping promoters (at 6 h with 125 nM NVS-BET-1 treatment compared to DMSO). Promoters defined as per NHEK ChromHMM, with top 100 down corresponding to 100 active promoters versus top 100 up classified as 25 active and 75 inactive promoters. Thick dotted lines represent median and thin dotted lines quartiles.
Extended Data Fig. 8 MSigDB gene set enrichment analysis.
(a) MSigDB gene set enrichment for genes significantly differentially expressed in keratinocytes with 6 h 125 nM NVS-BET-1 treatment versus DMSO control. Left panel shows enrichment of downregulated genes and right panel enrichment of upregulated genes using a hypergeometric test (b) Genes (highlighted in dark blue) from the ‘C2_ONDER_CDH1_Targets_2_DN’ gene signature (top gene set in Extended Data Fig. 4a left panel) projected onto global gene expression changes (RNA-seq, left panel) or onto gene-associated (based on proximity) BRD4 ChIP-seq peaks (right panel) after 6 h exposure to 125 nM NVS-BET-1 versus DMSO control (c) Genes (highlighted in dark blue) from the ‘C2-HELLER_HDAC_TARGETS_SILENCED_BY_METHYLATION_UP’ gene signature (top gene set in Extended Data Fig. 4a right panel) projected onto global gene expression changes (RNA-seq, left panel) or onto gene-associated (based on proximity) BRD4 ChIP-seq peaks (right panel) after 6 h exposure to 125 nM NVS-BET-1 versus DMSO control. ChIP-seq differential analysis was performed using DiffBind with DESeq2 (abs(log2FC) > 1 & p-value < 0.01). RNA-seq differential analysis was performed on the counts per million (CPMs) using a limma voom workflow with abs(log2FC) > 1 & adjusted p-value < 0.01. Dotted red lines indicate significance cut-offs.
Extended Data Fig. 9 Changes in chromatin accessibility induced in keratinocytes following low-dose exposure to BETi are reversible upon compound washout.
Genomic loci found differentially accessible by ATAC-seq in keratinocytes upon 6 h treatment with NVS-BET-1 (125 nM) compared to DMSO. Differential peaks were calculated with DiffBind using abs(log2FC) > 1 & p-value < 0.00001. Each row represents scaled and centered accessibility values across the different replicates shown in columns for DMSO and NVS-BET-1 at 6 h. Each row represents the normalized ATAC-seq signal across three different replicates per condition shown in columns. Differences between NVS-BET-1 and DMSO at 6 h are contrasted with accessibility values for NVS-BET-2 at 6 h and with accessibility values for all conditions after 42 h of compound washout (6m48h). First side heat map on right depicts differential signal (log2 fold change) per locus for 6 h NVS-BET-1 (125 nM) versus DMSO treatment. Second side heat map on far right provides ChromHMM annotation per genomic locus (row) according to ENCODE NHEK.
Extended Data Fig. 10 Acute skin wound healing after BETi treatment.
(a) Histological sections of mouse wounds 5 days after wounding. Samples were stained with H&E: Initial wound edge shown by a black triangle versus new wound edge indicated by a gray triangle were assigned to measure wound closure. All panels show re-epithelialization at Day 5. Top panels show 2 wounds after vehicle treatment on Day 1 and Day 3, middle panels show two wounds after two treatments with NVS-BET-1 at 3 mg/kg on Day 1 and Day 3 and the bottom panels show 2 wounds after two treatments with NVS-BET-2 at 1 mg/kg on Day 1 and Day 3. (b) Middle panel. Histological section of a mouse wound 5 days after wounding defining the areas termed epithelial tongue and wound edge. Sections from n = 5 wounds/group were stained by immunocytochemistry for Ki67, scanned and then analyzed by ImageJ 14.8 V with Immunoratio plugin. 2 images/wound were analyzed for the wound edge and up to 3 images/wound analyzed for epithelial tongue. Data shown represents image analysis for epithelial tongue (left) 0 mg/kg (vehicle) n = 10, NVS-BET-1 3 mg/kg n = 13 and NVS-BET-1 10 mg/kg (n = 10) and wound edge (right), n = 10 for all groups. The box extends from the 25th to 75th percentiles, center line shows median, and whiskers representing minimal and maximal value.
Supplementary information
Supplementary Information
Supplementary Figs. 1–7, Tables 1, 2 and 4, Datasets 1–4, Note 1 and References.
Supplementary Data 1
Biochemical selectivity profiles of NVS-BET-1 and NVS-BET-2 in DiscoverX BROMOscan assays.
Supplementary Data 2
RNA-seq profiles of keratinocytes after exposure to DMSO, JQ1 and NVS-BET-1 after 8 h.
Supplementary Data 3
RNA-seq profiles of keratinocytes after exposure to NVS-BET-1 for 6 h and 6m3h.
Supplementary Data 4
RNA-seq profiles of keratinocytes after exposure to NVS-BET-1 and NVS-BET-2 at 6 h and 42 h washout.
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Schutzius, G., Kolter, C., Bergling, S. et al. BET bromodomain inhibitors regulate keratinocyte plasticity. Nat Chem Biol 17, 280–290 (2021). https://doi.org/10.1038/s41589-020-00716-z
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DOI: https://doi.org/10.1038/s41589-020-00716-z
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