Single cell transcriptomics of human epidermis reveals basal stem cell transition states

Abstract

How stem cells give rise to human interfollicular epidermis is unclear despite the crucial role the epidermis plays in barrier and appendage formation. Here we use single cell-RNA sequencing to interrogate basal stem cell heterogeneity of human interfollicular epidermis and find at least four spatially distinct stem cell populations that decorate the top and bottom of rete ridge architecture and hold transitional positions between the basal and suprabasal epidermal layers. Cell-cell communication modeling through co-variance of cognate ligand-receptor pairs indicate that the basal cell populations distinctly serve as critical signaling hubs that maintain epidermal communication. Combining pseudotime, RNA velocity, and cellular entropy analyses point to a hierarchical differentiation lineage supporting multi-stem cell interfollicular epidermal homeostasis models and suggest the "transitional" basal stem cells are stable states essential for proper stratification. Finally, alterations in differentially expressed "transitional" basal stem cell genes result in severe thinning of human skin equivalents, validating their essential role in epidermal homeostasis and reinforcing the critical nature of basal stem cell heterogeneity. Joost et al., 2018). Despite these studies, epidermal stem cell heterogeneity of human IFE remains unresolved. To address this issue, we interrogated epidermal cell heterogeneity within human neonatal foreskin epidermis using droplet-enabled scRNA-seq and identify four spatially distinct basal stem cell subpopulations. Interrogation of the "transitional" basal subpopulations that spatially occupy both the basal and suprabasal layers indicate their essential role in epidermal homeostasis. Our findings argue against a single population of progenitor cells and suggest a more complex model of multiple epidermal stem cell transitions that maintain epidermal homeostasis. RESULTS Single cell transcriptome analysis reveals robust cellular heterogeneity in human neonatal epidermis.To define the cellular heterogeneity of human IFE, we isolated viable, single cells from discarded and de-identified human neonatal foreskin epidermis and subjected them to droplet-enabled scRNA-seq to resolve their individual transcriptomes ( Figure 1A; Supplementary Figure 1; Supplementary Table 1; n = 5). We chose foreskin epidermis because it is composed of mostly IFE and contains few rudimentary skin appendages, such as hair follicles and sweat glands (Tuncali et al., 2005). We processed a total of 17,553 cells and performed quality control analysis on individual libraries using Seurat (Supplementary Figure 2) (Macosko et al., 2015). We used Similarity matrix-based OPtimization for Single Cell (SoptSC) to bioinformatically parse and analyze our data . The SoptSC algorithm is based on a cell-cell similarity matrix that can coherently perform many inference tasks -including unsupervised clustering, pseudotemporal ordering, cell lineage inference, cell-cell communication, and network inference.We used library three as a repr...

Deciphering cell–cell interactions and communication from gene expression

“…CCC analysis also elucidated how erythroblasts interact with macrophages during haematopoiesis in the fetal liver 23 and was applied to liver organoid development to investigate how multilineage communication shapes the differentiation of hepatic cells 24 . Following similar principles, other studies have used CCC analyses to understand differentiation during epidermal regeneration 25 – 27 , development of the interfollicular epidermis 28 and formation of the maternal–fetal interface in early pregnancy 29 , 30 .…”

Single-cell analysis reveals MHCII expressing keratinocytes in pressure ulcers with worse healing outcomes

“…In the interfollicular epidermis of human skin, stem cells reside at the basal layer and exhibit cell heterogeneity (8). Our study revealed two keratinocyte clusters, KC_2 and KC_4, both of which strongly express the known basal keratinocyte signature, that is, KRT14, ITGA6, and ITGB1 (23, 24) (Figure 2I).…”

“…This dataset can be explored at a free, browsable web portal (https://www.xulandenlab.com/data). The advancement of single-cell RNA sequencing (scRNA-seq) technology has enabled the generation of molecular maps of human tissues at an unprecedented resolution, and this technology has recently been used to characterize human skin (5)(6)(7)(8) and related diseases, such as psoriasis (5), atopic dermatitis (9), and melanoma (10), as well as fibroblast heterogeneity (11) and epidermal stem cells (12,13) in murine wound models. Although rodent wound models exhibit a wound healing procedure similar to that of humans, they cannot fully reflect the complexity of disordered wound healing in humans (14,15).…”

Cellular heterogeneity and microenvironmental control of skin cancer

“…However, it remains elusive whether only cells that occupy specific niches or locations relative to the underlying dermis have SC properties, or if in principle all IFE basal cells are equally capable of responding to inductive signals and thus can serve as IFE SCs [9,109,110]. In human skin, earlier studies concluded that adult IFE SCs unlikely occupy specific locations in the basal epidermal layer [111,112], while recent single-cell RNA sequencing (scRNA-seq) analysis of human neonatal foreskin identified four basal cell subsets and the study overall suggests that specific niches may exist depending on the proximity to the so-called rete ridges (protrusions of the epidermis extending downwards into the dermal layer), with one population possibly associated with papillary fibroblasts [113]. In mouse skin, scRNA-seq identified two robust basal epidermal subsets of IFE cells (regardless of cell cycle) which differ in expression levels of typical basal epidermal genes (e.g.…”