Deciphering the functional heterogeneity of skin fibroblasts using single‐cell RNA sequencing

Abstract

Though skin fibroblasts (FB) are the main cell population within the dermis, the different skin FB subsets are not well characterized and the traditional classification into reticular and papillary FBs has little functional relevance. To fill the gap of knowledge on FB diversity in human skin, we performed single‐cell RNA sequencing. Investigation of marker genes for the different skin cell subtypes revealed a heterogeneous picture of FBs. When mapping reticular and papillary FB markers, we could not detect cluster specificity, suggesting that these two populations show a higher transcriptional heterogeneity than expected. This finding was further confirmed by in situ hybridization, showing that DPP4 was expressed in both dermal layers. Our analysis identified six FB clusters with distinct transcriptional signatures. Importantly, we could demonstrate that in human skin DPP4+ FBs are the main producers of factors involved in extracellular matrix (ECM) assembly. In conclusion, we provide evidence that hitherto considered FB markers are not ideal to characterize skin FB subpopulations in single‐cell sequencing analyses. The identification of DPP4+ FBs as the main ECM‐producing cells in human skin will foster the development of anti‐fibrotic treatments for the skin and other organs.

Single-Cell RNA Sequencing Unravels Heterogeneity of the Stromal Niche in Cutaneous Melanoma Heterogeneous Spheroids

“…A similar extent of fibroblast heterogeneity was also observed by other authors, who confirmed the polarisation of normal dermal fibroblasts to those producing ECM and fibroblasts producing pro-inflammatory factors. Of note, the particular composition of the proposed clusters was age-dependent [51,52]. This was also demonstrated in our study, comparing JDF and PDF.…”

Dissecting Fibroblast Heterogeneity in Health and Fibrotic Disease

“…Comparing young and old human skin in an extensive RNA-seq analysis Solé-Boldo et al, identified four major dermal fibroblast populations with functionally distinct transcriptomic signatures and spatial distribution and defined these as secretory-reticular, secretory-papillary, pro-inflammatory and mesenchymal fibroblasts [24]. Notably, another RNA-seq study mapping six distinct fibroblast populations in human skin failed to correlate established human papillary and reticular fibroblast markers to any specific clusters [25]. This perhaps indicates that the fibroblast transcriptome is strongly influenced by other factors, such as tissue state and biopsy location (Fig.…”

Single cell sequencing identifies serine proteases as regulators of myofibroblast differentiation

“…Our combined study of human mature hypertrophic scars and scar maturation in mice identified a group of serine proteases as key player for scar development and maturation. Although, DPP4positive FBs have previously been identified as the main source of ECM production in the skin 56 , and urokinase has been shown to be involved in lung fibrosis 19 , their roles in myofibroblast differentiation and production of ECM are still unclear. Our finding that addition of specific DPP4 and urokinase inhibitors to TGF1-stimulated FBs almost completely inhibited myofibroblast differentiation and up-regulation of matrix proteins was striking.…”

“…To elucidate the complex biological processes of scar formation, we performed droplet-based singlecell transcriptome analysis of human hypertrophic scar tissue and healthy skin 44 To identify the strongest differences in gene expression between normal skin and scars, we calculated all up-and downregulated genes for FBs, PCs, ECs, T-cells, DCs and KCs ( Figure S2). In general, we identified considerably more up-( Figure 1G) than downregulated genes ( Figure 1H), and the most abundant differential gene expression of scar compared to skin (number of differentially expressed genes, nDEG) was found in FBs, SMC/pericytes, macrophages, DC1 and KC1 ( Figure 1G, H).…”