Decoding the heterogeneity of skin in homeostasis and regeneration at single-cell resolution

Abstract

The skin plays a critical role in securing homeostasis in the mammalian body. Its epidermis forms a tight barrier, which separates the internal from the external environment, thereby shielding the body from physical and chemical insult. Due to the exposed position of skin as the outermost organ of the body, skin cells need to be replaced continuously. Cellular maintenance and regeneration of the skin and its associated hair follicles is orchestrated by a variety of stem cell populations. Because of its regenerative properties, the mouse skin is one of the most important model organs in stem cell research and regenerative medicine.

The skin is a complex multicellular system composed of a large variety of molecularly and functionally distinct cell populations. The physiology of the skin is a result of the intricate interplay of these diverse cell types. Accordingly, knowledge about the cellular composition of the skin is an essential step in understanding its biology. For a long time, cell populations in the skin were defined based on the expression of individual molecular markers, thus making a comprehensive analysis of cellular heterogeneity impossible. In this thesis, I describe how we used single-cell transcriptomics to create systematic cell type maps of the skin in order to analyze complex molecular processes at single-cell resolution.

In the first part of this thesis, I provide an overview of the morphology, function and cellular heterogeneity of the skin. I put particular emphasis on the skin as a self-maintaining tissue and model organ for stem cell research, describing regenerative process such as skin barrier maintenance, cyclical regeneration of hair follicles and cutaneous wound healing in great detail. Then, I introduce single-cell RNA-sequencing as a technique, which has revolutionized the way we analyze and conceptualize cellular heterogeneity in complex tissues.

Next, I portray how we championed the application of single-cell transcriptomics in skin biology with three key papers. In Paper I, we used single-cell RNA-sequencing to analyze the mouse epidermis including hair follicles during its resting stage (telogen). We discovered previously unknown cellular heterogeneity in the epidermis and demonstrated that the complexity of this tissue is the result of just two vectors of variation: differentiation stage and spatial position. In Paper II, we analyzed the complete mouse skin, including both epidermal and stromal cells, during hair growth (anagen) and rest (telogen). In addition to describing novel cell types in the stromal part of the skin, we model cellular differentiation and lineage specification in the growing hair follicle at unprecedented resolution. In Paper III, we use single-cell transcriptomics to track molecular changes in different stem cell populations during wound healing and answer several key questions related to stem cell identity and plasticity during regenerative processes.

In the last section of this thesis, I demonstrate that our studies have not just allowed us to analyze the cellular heterogeneity of the mouse skin at unprecedented detail, but have also enabled us to address a variety of critical questions such as how stem cell identity is shaped and how regenerative processes are orchestrated in the skin. I thus outline how our endeavors mark the first step towards a systems biology of the skin.