SCAnED - An Open-source Skin Segmentation Macro for Semi-automated Cell and Nuclei Detection in Epidermal and Dermal Skin Compartments

The spatial distribution of immune and non-immune cells within tissues and the expression of cell-specific markers provides essential information on cell function in situ. Human skin is a highly complex organ with defined compartments comprising different cells with diverse phenotypes. By using multi-fluorescence labeling, distinct skin cell populations can be determined and further characterized. However, currently, the availability of non-commercial tools for image analysis of skin samples that allow in silico segmentation of cells specifically within the epidermis or the dermis at a single-cell resolution is limited. We provide here a step-by-step protocol for immunofluorescence staining of skin sections, confocal microscopy, and image analysis using our freely available tool SCAnED (Skin Compartment Analysis of Epidermis and Dermis). The SCAnED macro allows the precise identification and classification of cells and nuclei in both the epidermal and dermal compartments of human skin. We provide guidelines on how to determine average intensity levels of maker expression in different cells and cellular compartments, such as the cytoplasm and the nucleus, and how to quantify cells expressing varying amounts of these markers with an accompanying Python pipeline provided as a ready-to-use Jupyter notebook executed in Google Colab. This protocol will allow inexperienced users to determine cell-specific expression profiles within skin tissue and provide insights into the spatial distribution of cells within the epidermal and dermal compartments, allowing a deeper understanding of the intricate tissue structure and cell composition of human skin.