Transcriptional Programming of Normal and Inflamed Human Epidermis at Single-Cell Resolution

Abstract

SUMMARY Perturbations in the transcriptional programs specifying epidermal differentiation cause diverse skin pathologies ranging from impaired barrier function to inflammatory skin disease. However, the global scope and organization of this complex cellular program remain undefined. Here we report single-cell RNA sequencing profiles of 92,889 human epidermal cells from 9 normal and 3 inflamed skin samples. Transcriptomics-derived keratinocyte subpopulations reflect classic epidermal strata but also sharply compartmentalize epithelial functions such as cell-cell communication, inflammation, and WNT pathway modulation. In keratinocytes, ~12% of assessed transcript expression varies in coordinate patterns, revealing undescribed gene expression programs governing epidermal homeostasis. We also identify molecular fingerprints of inflammatory skin states, including S100 activation in the interfollicular epidermis of normal scalp, enrichment of a CD1C+CD301A+ myeloid dendritic cell population in psoriatic epidermis, and IL1βhi CCL3hiCD14+ monocyte-derived macrophages enriched in foreskin. This compendium of RNA profiles provides a critical step toward elucidating epidermal diseases of development, differentiation, and inflammation.

Interleukin‐17A suppresses granular layer formation in a 3‐D human epidermis model through regulation of terminal differentiation genes

“…) . Consistent with our results, SPRR2D and SPRR2A have also been reported to be upregulated in the spinous and granular layers of psoriatic skin, which was analyzed at a single‐cell resolution . Regarding the downregulation of FLG, Gutowska‐Owsiak et al.…”

A hierarchy of migratory keratinocytes maintains the tympanic membrane

“…Thus, the pars flaccida exhibits both differentiation and stratification, whereas the pars tensa exhibits minimal stratification, but preserves aspects of predominantly early differentiation. Overall, the gene expression profiles obtained among the keratinocytes were similar to those previously observed in other interfollicular epidermal sites (Cheng et al 2018;Joost et al 2016;Joost et al 2018;Aragona et al 2017).…”

Riemannian geometry and statistical modeling correct for batch effects and control false discoveries in single-cell surface protein count data from CITE-seq

“…Our probabilistic modeling of ADT sequencing addresses this gap and also provides an appealing data representation based on the posterior mean E[λ], which can be used for down- Unlike the original approach [1], some CITE-seq data may lack a spike-in control from another species. In those cases, we recommend first finding a set of non-immune cells (e.g., erythrocytes in the blood, and keratinocytes in the skin [16,17]) that are transcriptomically distinct from the rest of the cells, and then using the set to build the null model for immunophenotype profiling. If this strategy is not feasible, then an unsupervised method could be developed to distinguish signal from noise by fitting bimodal or multimodal distributions.…”