Single-cell transcriptomics applied to emigrating cells from psoriasis elucidate pathogenic versus regulatory immune cell subsets. Academic Article uri icon

Overview

abstract

  • BACKGROUND: In previous human skin single-cell data, inflammatory cells constituted only a small fraction of the overall cell population, such that functional subsets were difficult to ascertain. OBJECTIVE: Our aims were to overcome the aforesaid limitation by applying single-cell transcriptomics to emigrating cells from skin and elucidate ex vivo gene expression profiles of pathogenic versus regulatory immune cell subsets in the skin of individuals with psoriasis. METHODS: We harvested emigrating cells from human psoriasis skin after incubation in culture medium without enzyme digestion or cell sorting and analyzed cells with single-cell RNA sequencing and flow cytometry simultaneously. RESULTS: Unsupervised clustering of harvested cells from psoriasis skin and control skin identified natural killer cells, T-cell subsets, dendritic cell subsets, melanocytes, and keratinocytes in different layers. Comparison between psoriasis cells and control cells within each cluster revealed that (1) cutaneous type 17 T cells display highly differing transcriptome profiles depending on IL-17A versus IL-17F expression and IFN-γ versus IL-10 expression; (2) semimature dendritic cells are regulatory dendritic cells with high IL-10 expression, but a subset of semimature dendritic cells expresses IL-23A and IL-36G in psoriasis; and (3) CCL27-CCR10 interaction is potentially impaired in psoriasis because of decreased CCL27 expression in basal keratinocytes. CONCLUSION: We propose that single-cell transcriptomics applied to emigrating cells from human skin provides an innovative study platform to compare gene expression profiles of heterogenous immune cells in various inflammatory skin diseases.

publication date

  • April 29, 2021

Research

keywords

  • Dendritic Cells
  • Psoriasis
  • Skin
  • Th17 Cells

Identity

Scopus Document Identifier

  • 85106971680

Digital Object Identifier (DOI)

  • 10.1016/j.jaci.2021.04.021

PubMed ID

  • 33932468

Additional Document Info