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Epigenomic signatures underpin the axonal regenerative ability of dorsal root ganglia sensory neurons

Nature Neuroscience volume 22, pages 1913–1924 (2019)Cite this article

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Abstract

Axonal injury results in regenerative success or failure, depending on whether the axon lies in the peripheral or the CNS, respectively. The present study addresses whether epigenetic signatures in dorsal root ganglia discriminate between regenerative and non-regenerative axonal injury. Chromatin immunoprecipitation for the histone 3 (H3) post-translational modifications H3K9ac, H3K27ac and H3K27me3; an assay for transposase-accessible chromatin; and RNA sequencing were performed in dorsal root ganglia after sciatic nerve or dorsal column axotomy. Distinct histone acetylation and chromatin accessibility signatures correlated with gene expression after peripheral, but not central, axonal injury. DNA-footprinting analyses revealed new transcriptional regulators associated with regenerative ability. Machine-learning algorithms inferred the direction of most of the gene expression changes. Neuronal conditional deletion of the chromatin remodeler CCCTC-binding factor impaired nerve regeneration, implicating chromatin organization in the regenerative competence. Altogether, the present study offers the first epigenomic map providing insight into the transcriptional response to injury and the differential regenerative ability of sensory neurons.

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Fig. 1: ATAC-seq, ChIP-seq and RNA-seq datasets.
Fig. 2: Peripheral but not central axotomy induces an increased chromatin accessibility and histone H3 acetylation.
Fig. 3: Peripheral but not central axotomy induces a robust transcriptional response in DRGs.
Fig. 4: Functional gene categories share a similar epigenetic signature.
Fig. 5: Specific enhancers respond to axonal injury.
Fig. 6: Footprinting analysis identifies specific clusters of TFs after axonal injury.
Fig. 7: Random forest classification differentiates between up- and downregulated genes based on TF footprints.
Fig. 8: CTCF is required for neurite outgrowth and nerve regeneration.

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Data availability

RNA-seq, ChIP-seq and ATAC-seq data have been deposited at the GEO under accession IDs GSE97090, GSE108806 and GSE132382. For detailed information on experimental design, please see the provided Nature Research Reporting Summary. Uncropped blots with molecular weight standards are provided in Supplementary Fig. 11.

Code availability

All code for processing and analyzing the data presented in this work are available on reasonable request.

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Acknowledgements

We would like to acknowledge the start-up funds: Division of Brain Sciences, Imperial College London (S.D.G.), Wings for Life grant no. WFL-UK-07/16 (S.D.G.), Rosetrees Trust grant no. A1438 (S.D.G.), the Leverhulme Trust grant no. RPG-2015-092 (S.D.G.), ISRT (S.D.G.), the Medical Research Council grant no. R/R005311/1 (S.D.G.) and WT grant no. 099276/Z/12/Z (M.M.). The research was supported by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (S.D.G.). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We thank C. Sibley, Imperial College London, for useful discussion and suggestions.

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Author notes

  1. These authors contributed equally: Ilaria Palmisano, Matt C. Danzi.

Authors and Affiliations

  1. Division of Neuroscience, Department of Brain Sciences, Imperial College London, London, UK

    Ilaria Palmisano, Thomas H. Hutson, Luming Zhou, Eilidh McLachlan, Elisabeth Serger, Arnau Hervera & Simone Di Giovanni

  2. The Miami Project to Cure Paralysis, University of Miami, Miami, FL, USA

    Matt C. Danzi, Nick O’ Neill, John L. Bixby & Vance P. Lemmon

  3. Center for Computational Science, University of Miami, Miami, FL, USA

    Matt C. Danzi, Stefan Wuchty, John L. Bixby & Vance P. Lemmon

  4. Integrative Genomics and Medicine, Division of Neuroscience, Department of Brain Sciences, Imperial College London, London, UK

    Kirill Shkura & Prashant K. Srivastava

  5. National Heart & Lung Institute, Imperial College London, London, UK

    Prashant K. Srivastava

  6. Molecular and Cellular Neurobiotechnology, Institute for Bioengineering of Catalonia, Barcelona, Spain

    Arnau Hervera

  7. Department of Computer Science, University of Miami, Miami, FL, USA

    Tong Liu, Hassen Dhrif, Zheng Wang & Stefan Wuchty

  8. Department of Electrical & Computer Engineering, University of Miami, Miami, FL, USA

    Miroslav Kubat

  9. Department of Biology, University of Miami, Miami, FL, USA

    Stefan Wuchty

  10. Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA

    Stefan Wuchty

  11. MRC London Institute of Medical Sciences, Imperial College London, London, UK

    Matthias Merkenschlager

  12. Faculty of Medicine, Bar Ilan University, Safed, Israel

    Liron Levi & Evan Elliott

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Contributions

I.P. designed and performed experiments, analyzed the data, and wrote and edited the manuscript. M.C.D. analyzed the data, and wrote and edited the manuscript. T.H.H. performed experiments, analyzed the data and edited the manuscript. L.Z. and E.S. performed experiments. E.M. performed experiments, analyzed the data and edited the manuscript. K.S. analyzed data and edited the manuscript. P.K.S. edited the manuscript. A.H. performed experiments and edited the manuscript. N.O. assisted with the data analysis and edited the manuscript. H.D., M.K. and S.W. performed the PSO analysis and edited the manuscript. T.L. and Z.W. performed the random forest analysis and edited the manuscript. M.M. and E.E. provided the CTCFflox/flox mice and discussed data analysis. L.L. maintained the CTCFflox/flox mice colony. J.L.B. and V.P.L. directed and interpreted experiments and edited the manuscript. S.D.G. designed experiments, and wrote and edited the manuscript.

Corresponding authors

Correspondence to Ilaria Palmisano or Simone Di Giovanni.

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The authors declare no competing interests.

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Peer review information Nature Neuroscience thanks E. Bradbury and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Integrated supplementary information

Supplementary Figure 1 Quality control and gene body analysis.

(A) Quantification of the recovered DNA after H3K9ac, H3K27ac, and H3K27me3 chromatin immunoprecipitation; IgG were used as negative control. Data is expressed as percentage with respect to Input (mean+s.e.m. of N=3 independent experiments, Pvalue: two-sided paired Student’s t-test; full statistics in Supplementary Data 15). (B) Heatmap of the ATACseq signal in each sample, as FPKM of reads within 1Kb of TSS of each gene, filtered for genes that are significantly DA after either SNA vs sham, or DCA vs lam. Colour is scaled by row (gene) with blue representing the lowest signal and red representing the highest signal. Clustering was performed using a Euclidean distance function. (C) Heatmaps showing genomic distribution of ATACseq signal, as Log2(Enrichment vs Background) (left) and H3K9ac, H3K27ac, and H3K27me3 histone mark signal, as Log2(IP vs Input) (right) in the Laminectomy control sample. (D) Line chart of the correlation in sham between the chromatin accessibility and the occupancy of the indicated histone marks in the gene body (percentile epigenetic signal, mean of N=3 for ATACseq, and N=2 for ChIPseq, independent samples) and the gene expression level (Log2FPKM, mean of N=3 independent samples); genes were divided in quartiles according to their expression level; Pvalue: 2-way ANOVA, Tukey’s multiple comparison test of the histone mark and ATAC signal in each quartile compared to the preceding one (ns=not significant); (full statistics in Supplementary Data 15). (E) Stacked bar plot of the number of genes with a differential occupancy of the indicated histone marks and chromatin accessibility at gene body upon SNA vs sham, or DCA vs lam (N=2 for ChIPseq, and N=3 for ATACseq, independent samples; Pvalue<0.05). (F) Area-proportional Venn diagram of the genes showing an increased H3K9ac and H3K27ac occupancy at both the TSS at gene body (N=2 independent samples; Pvalue<0.05). (G) Scatter plots of the histone mark occupancy in FPKM at the TSS (+−/1Kb) for the genes with increased (red dots) or decreased (blue dots) chromatin accessibility (N=3 independent samples; Pvalue<0.05).

Supplementary Figure 2 GO and KEGG analysis of DE genes upon SNA or DCA.

(A) Bar chart showing the first 10 ranked GO categories in the upregulated (red) and downregulated (blue) genes in SNA or DCA. (BP: Biological Process and MF: Molecular Function, Modified Fisher Exact Pvalue<0.01). (B) Heatmap showing the KEGG pathway categories in the DE genes in SNA or DCA (Modified Fisher Exact Pvalue<0.1).

Supplementary Figure 3 Correlation between gene expression and the four epigenomic features.

(A) Heatmap showing ATACseq and ChIPseq signal density for the up and downregulated genes upon DCA vs lam at equivalent genomic regions spanning from 2Kb upstream of the TSS to 2kb downstream of the TES. (B) Spearman correlation of the four epigenomic features (ATACseq, H3K9ac, H3K27ac, and H3K27me3 ChIPseq signal) with RNA expression level around the TSS of DE genes in the indicated conditions. (C) Integrative Genomic Viewer visualization of the ATACseq and ChIPseq signal density across the TSS and gene body of selected genes in the indicated conditions. Red box depicts TSS area.

Supplementary Figure 4 MS275 treatment only minimally mimics SNA.

(A-B) Cropped western blot (A) and quantification (B) of H3K9ac and H3K27ac expression following intraperitoneal MS275 injection after DCA. Uncropped version of the western blot is in Supplementary Fig. 11. In B, the levels of H3K9ac and H3K27ac have been normalized to total H3 and expressed as percentage vs vehicle, which is represented by the dotted red line (mean+s.e.m. of N=5 independent experiments; 1-way Anova, Dunnett’s multiple comparisons test; full statistics in Supplementary Data 15). (C) Bar plot of the number of genes with differential TSS accessibility (TSS+/−1Kb) (left) and differential expression (right) upon intraperitoneal MS275 injection after DCA injury vs vehicle (N=3 independent samples; Pvalue<0.05). (D) Odds ratio analysis of gene enrichment associated with a higher or lower chromatin accessibility at the TSS for upregulated, downregulated or non-DE genes upon MS275 treatment; the numbers represent the Pvalue, two-sided Fisher’s exact test (ns= not significant). (E) Bar chart showing the top ranked GO categories in the upregulated (red) and downregulated (blue) genes upon MS275 treatment (BP: Biological Process and MF: Molecular Function, Modified Fisher Exact Pvalue<0.01). (F-G) BaGfoot plots of the ΔFA (differential flanking accessibility) and ΔFPD (differential footprint depth) values of the motifs upon MS275 treatment at the level of TSS (TSS+/−1Kb) (F) and enhancers (G). The population median is marked in orange; the bag area (dark blue) represents the region where 50% of the motifs are located; the fence area (light blue) is the region where the remaining non-outlier motifs are located. The plots are divided in 4 quadrants (I-IV), and the red squares depict the statistically significant motifs outside the fence (Pvalue<0.05).

Supplementary Figure 5 Concordance between TF motif enrichment analysis and footprint data.

(A-B) Heatmap representing the enrichment (red, one-sided Fisher’s Exact Test multiple comparisons adjusted Pval<0.05) of the 150 top-ranked motifs in the DA regions (TSS+/-1Kb and enhancers), and in the DE genes (TSS+/-1Kb), the footprints calculated by HINT (purple, occupational score), and the relative TF expression level (turquoise, FPKM), after SNA vs sham (A), or DCA vs lam (B). For each TF, the highest occupational score has been reported.

Supplementary Figure 6 TF expression in DRG and footprint score correlation.

(A-B) Scatterplot of the change in footprint score distribution (quantified by the Kolmogorov-Smirnov test) vs Log2(Fold Change) in gene expression for TFs in SNA vs sham (A, 100 TFs), or DCA vs lam (B, 103 TFs). Only TFs with FPKM>6 in conditions being compared were used. Linear fit of data points is plotted in red. Spearman correlation of the data values is shown in the upper right corner of each plot. (C) Area-proportional Venn diagrams showing the number of TFs identified in DRG (left) and DE genes after SNA and DCA (right) expressed in neuronal populations. The genes expressed in neurons (green circle) were retrieved from Usoskin et al., Nature Neuroscience, 18, 145–153 (2015).

Supplementary Figure 7 CTCF BS are enriched at regenerative genes.

(A) Stacked bar plot illustrating the number of genes with CTCF BS in the TSS +/-1Kb region with a differential chromatin accessibility and occupancy of the indicated histone marks upon SNA vs sham, or DCA vs lam (N=3 for ATACseq, and N=2 for ChIPseq, independent samples; Pvalue<0.05). (B) Stacked bar plot illustrating the number of enhancers with CTCF BS with a differential chromatin accessibility and occupancy of the indicated histone marks upon SNA vs sham, or DCA vs lam (N=3 for ATACseq, and N=2 for ChIPseq, independent samples; Pvalue<0.05). (C) Bar plot of the number of DE genes after SNA vs sham, or DCA vs lam with a CTCF BS (TSS and enhancers +/-1 Kb) (N=3 independent samples; Pvalue<0.05). (D) Heatmap comparing the GO enrichment analysis of the upregulated and downregulated genes upon SNA, with that of subset of genes with CTCF BS at their TSS or enhancer +/-1Kb, and with that of the upregulated and downregulated genes in mouse CTCF-cKO hippocampus (GSE84175) (BP:biological process, Modified Fisher Exact Pvalue<0.05). (E) Heatmap showing the upregulated RAGs, ranked by fold change; in purple the ones displaying CTCF BS at their TSS or enhancer +/-1Kb. (F) DNA quantification by RT-PCR of the recovered DNA after microccocal nuclease (MNase) treatment at different concentrations (U=units), relative to Input. The Fos TSS +/-1 Kb region has been tested following SNA (top) or DCA (bottom) vs their controls (mean+s.e.m. of N=3 independent experiments). (G) Ratio of the recovered DNA after MNase treatment at different concentrations upon SNA vs sham (top), or DCA vs lam (bottom) for the indicated TSS +/-1 Kb regions (mean±s.e.m. of; N=3 independent experiments for Klf16 and Bdnf upon SNA, for Bdnf upon DCA, for Klf16 and b2m at 1.5 U of MNase; N=4 for all the other conditions;2-way ANOVA, Sidak’s multiple comparison test; ns=not significant; full statistics in Supplementary Data 15. The red line represents a ratio=1, meaning no difference between conditions.

Supplementary Figure 8 Sensorimotor assessments.

CatWalk Automated Gait Analysis (A-F) and Von Frey (G) analysis of CTCF-cKO vs WT mice after SNC. Mice were assessed 1 day before injury, as baseline, and then at the indicated time points after SNC. (A) Run speed (the average speed of the recorded run; mean + s.e.m. of N=9 or 10 mice; 2-way ANOVA, Sidak’s multiple comparison test; ns=not significant; full statistics in Supplementary Data 15); (B) Max Intensity (maximum intensity of the complete paw; mean + s.e.m. of N=6 or 7 mice; 2-way ANOVA, Sidak’s multiple comparison test; ns=not significant; full statistics in Supplementary Data 15); (C) Max Contact Max Intensity (the maximum Intensity at maximum contact of the paw; mean + s.e.m. of N=6 or 7 mice; 2-way ANOVA, Sidak’s multiple comparison test; ns=not significant; full statistics in Supplementary Data 15); (D) Hind paw print width (the width of the complete paw print; mean + s.e.m. of N=6 or 7 mice; 2-way ANOVA, Sidak’s multiple comparison test; ns=not significant; full statistics in Supplementary Data 15); (a.u., aribitrary units); (E) Manual Print Length (the distance between the center of the third toe and the heel of a paw; mean + s.e.m. of N=12-20 prints; 2-way ANOVA, Turkeys’s multiple comparison test; ns=not significant; full statistics in Supplementary Data 15); (F) Intermediate Toe Spread (the distance between the center of the second and fourth toe of a hind paw; mean + s.e.m. of N=6-20 prints, 2-way ANOVA, Turkeys’s multiple comparison test; ns=not significant; full statistics in Supplementary Data 15); (G) The minimum force (g) applied in order to have a positive withdrawal response (mean + s.e.m. of N=9 mice; 2-way ANOVA, Sidak’s multiple comparison test; ns=not significant; full statistics in Supplementary Data 15).

Supplementary Figure 9 Dataset validation.

(A) Spearman correlation analysis between DE genes after SNA vs sham, or DCA vs lam (N=3 independent samples; Pvalue<0.05 or FDR<0.05) and published datasets (GSE30165, GSE21007, GSE26350, and GSE33175) including several models of sciatic nerve injury at several time points as downloaded from Gene Expression Omnibus (GEO). SNL: sciatic nerve ligation. GSE number and time points after injury are reported for each dataset. Colour code indicates the degree and direction of the correlation (red=positive; blue=negative). Grey indicates not applicable analysis (no datasets available). The numbers in black represent the Pvalue by two-sided Fisher’s exact test (blank= not significant). (B) Odds ratio analysis of the enrichment of upregulated and downregulated genes in our dataset (Pvalue<0.05) across each upregulated and downregulated gene clusters of the individual published datasets; the numbers in red represent the Pvalue given by two-sided Fisher’s exact test (blank= not significant). (C) Bar plot of the number of DE genes in DRG after SNA vs sham, or DCA vs lam using specific significance cut offs (N=3 independent samples; Pvalue<0.05; FDR<0.1; FDR<0.05). (D-E) mRNA quantification by RT-PCR of the indicated transcripts upon SNA vs sham (D), or DCA vs lam (E) relative to control injury and normalized vs GAPDH (mean+s.e.m. of N=3 independent experiments for SNA (except N=5 for Hdac4); N=4 independent experiments for DCA (except N=3 for Hdac5; N=7 for Capn11); two-sided unpaired Student’s t-test; ns=not significant; full statistics in Supplementary Data 15). The red line represents a ratio=1, meaning no difference between conditions. (F) H3K27ac ChIP quantification by RT-PCR of the indicated promoter regions upon SNA or Sham injury normalized vs total H3 ChIP (mean+s.e.m. of N=3 independent experiments; two-sided unpaired Student’s t-test; ns=not significant; full statistics in Supplementary Data 15).

Supplementary Figure 10 Summary.

Overview of the experimental design and the performed combinatorial genome-wide analysis.

Supplementary Figure 11 Uncropped Western blots.

Uncropped versions of the western blots in Supplementary Fig. 4a.

Supplementary Information

Supplementary Figs. 1–11, Supplementary Tables 1 and 2, Supplementary Methods and Supplementary Note 1.

Reporting Summary

Supplementary Dataset 1

Complete dataset of RNA-seq, ATAC-seq, H3K9ac, H3K27ac and H3K27me3 ChIP-seq signal intensities in each indicated condition for each replicate (n= 3 for RNA-seq and ATAC-seq; n = 2 for ChIP-seq, independent samples) at the level of TSS ± 1,000 bp and gene body. For each gene, the gene Ensembl ID, the gene name, the chromosome coordinates, the TSS coordinates, the strand, the signal intensity (FPKM), the log2(fold change) (FC), P value and FDR are given.

Supplementary Dataset 2

GO analysis using DAVID of genes showing a DA TSS on SNA or DCA (P < 0.05). For each GO term, the number of enriched genes (count), the percentage in the population, the P value, the gene Ensembl ID, the number of genes in the input list (list total), the hits in the population (pop hits), the total number in the population (pop total), the fold enrichment, and Bonferroni’s, Benjamini’s and FDR modified P values are shown. The statistically significant (modified Fisher exact P < 0.01) GO categories are highlighted in yellow.

Supplementary Dataset 3

GO and KEGG pathway analysis using DAVID of DE genes on SNA or DCA (P < 0.05). For each term, the number of enriched genes (count), the percentage in the population, the P value, the gene Ensembl ID, the number of genes in the input list (list total), the hits in the population (pop hits), the total number in the population (pop total), the fold enrichment, and Bonferroni’s, Benjamini’s and FDR modified P values are shown. The statistically significant (modified Fisher exact P < 0.01 for GO and 0.05 for KEGG) categories are highlighted in yellow.

Supplementary Dataset 4

GO enrichment analysis using DAVID of DE and differentially bound genes for each histone mark on SNA or DCA (P < 0.05). For each term, the number of enriched genes (count), the percentage in the population, the P value, the gene Ensembl ID, the number of genes in the input list (list total), the hits in the population (pop hits), the total number in the population (pop total), the fold enrichment, and Bonferroni’s, Benjamini’s and FDR modified P values are shown. The statistically significant (modified Fisher exact P < 0.01) GO categories are highlighted in yellow.

Supplementary Dataset 5

Complete dataset of ATAC-seq, H3K9ac, H3K27ac and H3K27me3 ChIP-seq signal intensities in each indicated condition for each replicate (n = 3 for ATAC-seq, n = 2 for ChIP-seq, independent samples) at the level of enhancers. For each enhancer the chromosome coordinates determined by ENCODE, the predicted target gene information, the identified peak, the log2(fold change) (FC), P value and FDR are given. Values were not reported for a given mark if no peak was observed within 1 kb of the enhancer in the examined conditions.

Supplementary Dataset 6

Output of the BaGfoot analysis of the ATAC-seq dataset after SNA or DCA at the level of enhancers and promoters.

Supplementary Dataset 7

List of DE and DA genes on MS275 treatment at the time of DCA versus vehicle. For each gene, the gene Ensembl ID, the gene name, the RNA and ATAC signal intensities at the level of TSS ± 1,000 bp, the log2(fold change) (FC), P value and FDR are given

Supplementary Dataset 8

List of the genes that are commonly DE on MS275 treatment and SNA.

Supplementary Dataset 9

GO analysis using DAVID of the DE and the DA genes on MS275 treatment after DCA versus vehicle (P < 0.05). For each term, the number of enriched genes (count), the percentage in the population, the P value, the gene Ensembl ID, the number of genes in the input list (list total), the hits in the population (pop hits), the total number in the population (pop total), the fold enrichment, and Bonferroni’s, Benjamini’s and FDR-modified P values are shown. The statistically significant (modified Fisher exact P < 0.01) categories are highlighted in yellow.

Supplementary Dataset 10

Output of the HINT analysis of the ATAC-seq dataset after SNA or DCA at the level of DA regions.

Supplementary Dataset 11

TF motif enrichment analysis performed with AME of the enhancer and TSS (±1 kb) regions with differential chromatin accessibility on SNA or DCA and at the level of TSS (±1 kb) regions of DE genes. One-sided Fisher’s exact test was performed against the Jaspar core 2016, using a background of shuffled input sequences.

Supplementary Dataset 12

List of the different TFs associated with the HINT footprints identified in DRGs after SNA or DCA. For each footprint, the related TF matrix with occupational score and gene target with gene expression and epigenetic modification data are given. For enhancer-associated footprints, the enhancer ID is also given (see also Methods).

Supplementary Dataset 13

List of CTCF BSs collected from CTCFBSDB2.0 (brain/cerebellum) and from the GEO (GSE84174) (hippocampus) databases, associated with TSS and enhancers (±1 kb). For each promoter and enhancer, information for the target gene is given.

Supplementary Dataset 14

GO analysis using DAVID of the differentially regulated genes on SNA or DCA (FDR < 0.05) that contain CTCF BSs at their promoter (TSS ± 1 kb) or enhancer (enhancer ± 1 kb), and of the differentially regulated genes in mouse CTCF-cKO hippocampus (GSE84175). In yellow, the statistically significant (modified Fisher exact P < 0.01) GO categories are highlighted.

Supplementary Dataset 15

Full statistics of all the experiments. The file reports the power level analysis of the dataset in terms of number of replicates (n) needed to obtain appropriate levels of power for several effect sizes for each of the four datasets. Power level at several effect sizes for increasing number of replicates is also reported. The full statistics of all experiments are reported.

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Palmisano, I., Danzi, M.C., Hutson, T.H. et al. Epigenomic signatures underpin the axonal regenerative ability of dorsal root ganglia sensory neurons. Nat Neurosci 22, 1913–1924 (2019). https://doi.org/10.1038/s41593-019-0490-4

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