Decoding cutaneous injury-induced inflammation through single-cell RNA sequencing

Tissue repair requires rapid transitions in cellular states and robust cellular communication between tissue-resident cells and infiltrating immune cells. After injury, the amplitude and temporal regulation of inflammation must be efficiently coordinated to support subsequent tissue repair. Single-cell RNA sequencing (scRNA-seq) technologies and computational data analysis approaches have generated predictions about cellular states and communication that control inflammation, thereby promoting wound healing. Using skin as a clinically relevant model, we discuss how scRNA-seq has advanced our understanding of mechanisms that regulate inflammation after injury. In this review, we provide a detailed description of validated markers used to identify distinct cellular populations in murine and human skin and discuss how scRNA-seq has deepened our understanding of mechanisms regulating inflammation during acute wound healing. We further describe insights gained from scRNA-seq data generated under pathological conditions associated with dysfunctional inflammation and delayed wound healing, such as diabetes and aging. Future validation of these computational predictions and overcoming limitations associated with single-cell transcriptomics will provide greater clinical relevance for this technology that has increased the depth and rate of scientific discovery.