Genome-wide DNA hypermethylation opposes healing in patients with chronic wounds by impairing epithelial-mesenchymal transition
Kanhaiya Singh, … , Sashwati Roy, Chandan K. Sen
Kanhaiya Singh, … , Sashwati Roy, Chandan K. Sen
Published July 12, 2022
Citation Information: J Clin Invest. 2022;132(17):e157279. https://doi.org/10.1172/JCI157279.
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Research Article Dermatology

Genome-wide DNA hypermethylation opposes healing in patients with chronic wounds by impairing epithelial-mesenchymal transition

Abstract

An extreme chronic wound tissue microenvironment causes epigenetic gene silencing. An unbiased whole-genome methylome was studied in the wound-edge tissue of patients with chronic wounds. A total of 4,689 differentially methylated regions (DMRs) were identified in chronic wound-edge skin compared with unwounded human skin. Hypermethylation was more frequently observed (3,661 DMRs) in the chronic wound-edge tissue compared with hypomethylation (1,028 DMRs). Twenty-six hypermethylated DMRs were involved in epithelial-mesenchymal transition (EMT). Bisulfite sequencing validated hypermethylation of a predicted specific upstream regulator TP53. RNA-Seq analysis was performed to qualify findings from methylome analysis. Analysis of the downregulated genes identified the TP53 signaling pathway as being significantly silenced. Direct comparison of hypermethylation and downregulated genes identified 4 genes, ADAM17, NOTCH, TWIST1, and SMURF1, that functionally represent the EMT pathway. Single-cell RNA-Seq studies revealed that these effects on gene expression were limited to the keratinocyte cell compartment. Experimental murine studies established that tissue ischemia potently induces wound-edge gene methylation and that 5′-azacytidine, inhibitor of methylation, improved wound closure. To specifically address the significance of TP53 methylation, keratinocyte-specific editing of TP53 methylation at the wound edge was achieved by a tissue nanotransfection-based CRISPR/dCas9 approach. This work identified that reversal of methylation-dependent keratinocyte gene silencing represents a productive therapeutic strategy to improve wound closure.

Authors

Kanhaiya Singh, Yashika Rustagi, Ahmed S. Abouhashem, Saba Tabasum, Priyanka Verma, Edward Hernandez, Durba Pal, Dolly K. Khona, Sujit K. Mohanty, Manishekhar Kumar, Rajneesh Srivastava, Poornachander R. Guda, Sumit S. Verma, Sanskruti Mahajan, Jackson A. Killian, Logan A. Walker, Subhadip Ghatak, Shomita S. Mathew-Steiner, Kristen E. Wanczyk, Sheng Liu, Jun Wan, Pearlly Yan, Ralf Bundschuh, Savita Khanna, Gayle M. Gordillo, Michael P. Murphy, Sashwati Roy, Chandan K. Sen

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Figure 3

Single-cell RNA-Seq analysis identifies 2 epithelial clusters in human unwounded skin, one of which, high in metabolic genes, is diminished in chronic WE tissue.

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Single-cell RNA-Seq analysis identifies 2 epithelial clusters in human u...
(A) tSNE (t-distributed stochastic neighbor embedding) plots showing single-cell transcriptomes of 25,561 cells from UW skin (obtained from 4 individuals) (left) and 25,168 cells from chronic WE (right) (obtained from 3 individuals) analyzed using the 10x Genomics platform. Unsupervised clustering revealed cellular heterogeneity with 11 distinct clusters of cells identified and color-coded. Each cell is represented as a dot. (B) tSNE clustering of the epithelial cells showing 2 identified keratinocytes, Kera1 (cluster 5) and Kera2 (cluster 6), in human UW skin. (C) Violin plots showing the expression level of the top 3 upregulated transcription regulators and (D) top 3 upregulated enzymes in the Kera2 cluster of human UW skin compared with the Kera1 cluster. (*adjusted P < 0.00001, Wilcoxon rank-sum test). (E) Heatmap showing the relative expression of genes involved in cellular metabolism in the 2 keratinocyte clusters (Kera1 and Kera2). (F) Heatmap showing the relative expression of genes involved in glycolysis in the 2 keratinocyte clusters (Kera1 and Kera2). (G) Spatial transcriptomics identified distinct localization of Kera1 (marked by high KRT14 and KRT1 expression) and Kera2 (marked by high KRT19 and KRT7 expression) in human UW skin through spatial feature plots. Scale bar for expression levels: KRT14 (scale: 0–3), KRT1 (scale: 0–2), KRT19 (scale: 0–1.5), and KRT7 (scale: 0–1.6). H&E staining of human skin section (left) was processed for Visium spatial gene expression analysis for classifying tissue based on mRNA levels. Further characterization of the Kera2 cluster is illustrated in Supplemental Figure 4A.