Dataset Information

Single cell transcriptomics of human epidermis identifies basal stem cell transition states.

ABSTRACT: How stem cells give rise to 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 four spatially distinct stem cell populations at the top and bottom of rete ridges and transitional positions between the basal and suprabasal epidermal layers. Cell-cell communication modeling suggests that basal cell populations serve as crucial signaling hubs to 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 that 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.

SUBMITTER: Wang S

PROVIDER: S-EPMC7447770 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Single cell transcriptomics of human epidermis identifies basal stem cell transition states.

Wang Shuxiong S Drummond Michael L ML Guerrero-Juarez Christian F CF Tarapore Eric E MacLean Adam L AL Stabell Adam R AR Wu Stephanie C SC Gutierrez Guadalupe G That Bao T BT Benavente Claudia A CA Nie Qing Q Atwood Scott X SX

Nature communications 20200825 1

How stem cells give rise to 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 four spatially distinct stem cell populations at the top and bottom of rete ridges and transitional positions between the basal and suprabasal epidermal layers. Cell-cell communication modeling suggests that basal cell populations serve as cr ...[more]

PMID: 32843640

Similar Datasets

Project description:Similarities between stem cells and cancer cells have implicated mammary stem cells in breast carcinogenesis. Recent evidence suggests that normal breast stem cells exist in multiple phenotypic states: epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M). Hybrid E/M cells in particular have been implicated in breast cancer metastasis and poor prognosis. Mounting evidence also suggests that stem cell phenotypes change throughout the life course, for example, through embryonic development and pregnancy. The goal of this study was to use single cell RNA-sequencing to quantify cell state distributions of the normal mammary (NM) gland throughout developmental stages and when perturbed into a stem-like state in vitro using conditional reprogramming (CR). Using machine learning based dataset alignment, we integrate multiple mammary gland single cell RNA-seq datasets from human and mouse, along with bulk RNA-seq data from breast tumors in the Cancer Genome Atlas (TCGA), to interrogate hybrid stem cell states in the normal mammary gland and cancer. CR of human mammary cells induces an expanded stem cell state, characterized by increased expression of embryonic stem cell associated genes. Alignment to a mouse single-cell transcriptome atlas spanning mammary gland development from in utero to adulthood revealed that NM cells align to adult mouse cells and CR cells align across the pseudotime trajectory with a stem-like population aligning to the embryonic mouse cells. Three hybrid populations emerge after CR that are rare in NM: KRT18+/KRT14+ (hybrid luminal/basal), EPCAM+/VIM+ (hybrid E/M), and a quadruple positive population, expressing all four markers. Pseudotime analysis and alignment to the mouse developmental trajectory revealed that E/M hybrids are the most developmentally immature. Analyses of single cell mouse mammary RNA-seq throughout pregnancy show that during gestation, there is an enrichment of hybrid E/M cells, suggesting that these cells play an important role in mammary morphogenesis during lactation. Finally, pseudotime analysis and alignment of TCGA breast cancer expression data revealed that breast cancer subtypes express distinct developmental signatures, with basal tumors representing the most "developmentally immature" phenotype. These results highlight phenotypic plasticity of normal mammary stem cells and provide insight into the relationship between hybrid cell populations, stemness, and cancer.

Dataset Information

Single cell transcriptomics of human epidermis identifies basal stem cell transition states.

Publications

Single cell transcriptomics of human epidermis identifies basal stem cell transition states.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets