A Roadmap for a Consensus Human Skin Cell Atlas and Single-Cell Data Standardization

Abstract

Single-cell technologies have become essential to driving discovery in both basic and translational investigative dermatology. Despite the multitude of available datasets, a central reference atlas of normal human skin, which can serve as a reference resource for skin cell types, cell states, and their molecular signatures, is still lacking. For any such atlas to receive broad acceptance, participation by many investigators during atlas construction is an essential prerequisite. As part of the Human Cell Atlas project, we have assembled a Skin Biological Network to build a consensus Human Skin Cell Atlas and outline a roadmap toward that goal. We define the drivers of skin diversity to be considered when selecting sequencing datasets for the atlas and list practical hurdles during skin sampling that can result in data gaps and impede comprehensive representation and technical considerations for tissue processing and computational analysis, the accounting for which should minimize biases in cell type enrichments and exclusions and decrease batch effects. By outlining our goals for Atlas 1.0, we discuss how it will uncover new aspects of skin biology. Single-cell technologies have become essential to driving discovery in both basic and translational investigative dermatology. Despite the multitude of available datasets, a central reference atlas of normal human skin, which can serve as a reference resource for skin cell types, cell states, and their molecular signatures, is still lacking. For any such atlas to receive broad acceptance, participation by many investigators during atlas construction is an essential prerequisite. As part of the Human Cell Atlas project, we have assembled a Skin Biological Network to build a consensus Human Skin Cell Atlas and outline a roadmap toward that goal. We define the drivers of skin diversity to be considered when selecting sequencing datasets for the atlas and list practical hurdles during skin sampling that can result in data gaps and impede comprehensive representation and technical considerations for tissue processing and computational analysis, the accounting for which should minimize biases in cell type enrichments and exclusions and decrease batch effects. By outlining our goals for Atlas 1.0, we discuss how it will uncover new aspects of skin biology. The skin contains diverse cell lineages, including epithelial cells of the epidermis and ectodermal appendages—hair follicles, nails, sebaceous glands, and sweat glands—which exist in close association with mesenchymal cell lineages, including smooth muscle cells, adipocytes, and fibroblasts. The latter produces extracellular matrix for mechanical support and signals that guide immune and epithelial cell behavior across both spatial dimensions of the skin (e.g., epidermal differentiation at the surface) and time (e.g., cyclic growth of hair follicles). In addition to the principal skin cell types, there are less abundant cell types essential for skin function, including pigment-producing melanocytes, innate and adaptive immune cells, vascular and perivascular cells, and cells of neuroendocrine origin. Working together, these cell populations form a barrier organ—so large that no individual dataset can sample the entire skin—that plays mechanoprotective, UV-shielding, antimicrobial, thermoregulatory functions and more (Alexander et al., 2015Alexander C.M. Kasza I. Yen C.L.E. Reeder S.B. Hernando D. Gallo R.L. et al.Dermal white adipose tissue: a new component of the thermogenic response.J Lipid Res. 2015; 56: 2061-2069Abstract Full Text Full Text PDF PubMed Scopus (77) Google Scholar; Donati et al., 2017Donati G. Rognoni E. Hiratsuka T. Liakath-Ali K. Hoste E. Kar G. et al.Wounding induces dedifferentiation of epidermal Gata6+ cells and acquisition of stem cell properties.Nat Cell Biol. 2017; 19: 603-613Crossref PubMed Scopus (97) Google Scholar; Gurtner et al., 2008Gurtner G.C. Werner S. Barrandon Y. Longaker M.T. Wound repair and regeneration.Nature. 2008; 453: 314-321Crossref PubMed Scopus (4094) Google Scholar; Takeo et al., 2015Takeo M. Lee W. Ito M. Wound healing and skin regeneration.Cold Spring Harb Perspect Med. 2015; 5: a023267Crossref PubMed Google Scholar; Watt, 2014Watt F.M. Mammalian skin cell biology: at the interface between laboratory and clinic.Science. 2014; 346: 937-940Crossref PubMed Scopus (138) Google Scholar). To support these functions, different skin compartments are richly populated by stem cells that respond to insults by mounting reparative responses. As the skin heals, such as after wounding, it restores anatomical integrity and functions by forming a scar containing new stable cell states that are distinct from unwounded cell states (Donati et al., 2017Donati G. Rognoni E. Hiratsuka T. Liakath-Ali K. Hoste E. Kar G. et al.Wounding induces dedifferentiation of epidermal Gata6+ cells and acquisition of stem cell properties.Nat Cell Biol. 2017; 19: 603-613Crossref PubMed Scopus (97) Google Scholar; Gurtner et al., 2008Gurtner G.C. Werner S. Barrandon Y. Longaker M.T. Wound repair and regeneration.Nature. 2008; 453: 314-321Crossref PubMed Scopus (4094) Google Scholar; Sun et al., 2022Sun X. Joost S. Kasper M. Plasticity of epithelial cells during skin wound healing [epub ahead of print].Cold Spring Harb Perspect Biol. 2022; (accessed March 17, 2023)https://doi.org/10.1101/cshperspect.a041232Crossref Scopus (2) Google Scholar; Takeo et al., 2015Takeo M. Lee W. Ito M. Wound healing and skin regeneration.Cold Spring Harb Perspect Med. 2015; 5: a023267Crossref PubMed Google Scholar). Several hundred clinically distinct disorders, both monogenic and multifactorial, affect human skin (Feramisco et al., 2009Feramisco J.D. Sadreyev R.I. Murray M.L. Grishin N.V. Tsao H. Phenotypic and genotypic analyses of genetic skin disease through the Online Mendelian Inheritance in Man (OMIM) database.J Invest Dermatol. 2009; 129: 2628-2636Abstract Full Text Full Text PDF PubMed Scopus (48) Google Scholar). Although many skin diseases are well-characterized clinically, histologically, genetically, and by bulk biochemical assays, deep mechanistic understanding remains obscured in part by a lack of characterization at single-cell resolution. Moreover, numerous distinct diseases have near-identical clinical manifestations (Feramisco et al., 2009Feramisco J.D. Sadreyev R.I. Murray M.L. Grishin N.V. Tsao H. Phenotypic and genotypic analyses of genetic skin disease through the Online Mendelian Inheritance in Man (OMIM) database.J Invest Dermatol. 2009; 129: 2628-2636Abstract Full Text Full Text PDF PubMed Scopus (48) Google Scholar; Lamartine, 2003Lamartine J. Towards a new classification of ectodermal dysplasias.Clin Exp Dermatol. 2003; 28: 351-355Crossref PubMed Scopus (153) Google Scholar), challenging correct diagnosis and resulting in ineffective therapies. Certain diseases, such as psoriasis, are spatially predisposed to appear in certain body regions (Dhabale and Nagpure, 2022Dhabale A. Nagpure S. Types of psoriasis and their effects on the immune system.Cureus. 2022; 14e29536Google Scholar). Other diseases, such as facial acne, disproportionately occur at certain ages (Williams et al., 2012Williams H.C. Dellavalle R.P. Garner S. Acne vulgaris.Lancet. 2012; 379: 361-372Abstract Full Text Full Text PDF PubMed Scopus (737) Google Scholar), and other diseases occur more commonly in females than in males, such as scleroderma (Andersen and Davis, 2016Andersen L.K. Davis M.D.P. Sex in the of skin and diseases in and a with other Dermatol. 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