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Single-Cell Study Discovers Diversity in Wound Healing Cells of Mice

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Summary

In the course of wound healing, adipocytes, and hair follicles undergo regeneration in adult mouse skin. Adipocytes arise from myofibroblasts, a specialized wound fibroblast type that is contractile. The authors investigated the diversity of wound fibroblasts using single-cell RNA sequencing. They identified twelve clusters of wound fibroblasts. Pseudotime and RNA velocity analyses suggested that some of these clusters may represent sequential differentiation states towards a contractile phenotype, while others appeared to derive from distinct fibroblast lineages. Hematopoietic markers were expressed by a subset of fibroblasts, indicating their myeloid origin. This finding was corroborated using single-cell western blot and single-cell RNA-sequencing on genetically labeled myofibroblasts. Through bone marrow transplantation and Cre recombinase-based lineage tracing experiments, they demonstrated that hematopoietic lineage cells give rise to a subset of myofibroblasts and rare regenerated adipocytes, and ruled out cell fusion events. Overall, their study highlights the high degree of heterogeneity among fibroblasts during wounding and the recruitment of highly plastic myeloid cells that contribute to adipocyte regeneration.

Research Criteria

In recent years, significant strides have been made in uncovering the various signaling pathways involved in wound-induced hair neogenesis (WIHN). While the activation of canonical WNT signaling is an essential component of this process, it is not yet clear how cells from different lineages contribute to WIHN. This knowledge gap may be addressed by the advent of single cell RNA sequencing (scRNA-seq), which allows the identification of cell types and their heterogeneity in tissues with poorly characterized cellular compositions. Here, using scRNA-seq, the authors identify and characterize various distinct fibroblast subpopulations that contribute to the regeneration of mouse wounds.

Experimental design.Fig.1 Experimental design. (Guerrero-Juarez, 2019)

Sample Type

Cells from mouse skin.

Result—Single-Cell Analysis Reveals Heterogeneity in Large Wounds

In the present study, wound dermal cells from mice were examined using scRNA-seq technology 12 days after wounding (PW), when re-epithelialization had peaked and high SMA, a common hallmark of myofibroblasts, was expressed. Using Seurat-based unsupervised clustering methods, a total of 21,819 cells that passed quality control criteria and were analyzed were found to be clustered into thirteen separate groups. In later analyses, the researchers assigned clusters to their hypothesized cellular identities and clarified their hierarchical links using differentially expressed gene profiles. These discoveries offer a fundamental framework for categorizing cell types and gene expression patterns during wound healing.

scRNA-seq analysis reveals cellular heterogeneity in day 12 wounds.Fig.2 scRNA-seq analysis reveals cellular heterogeneity in day 12 wounds. (Guerrero-Juarez, 2019)

Result—Analyses Reveal Myofibroblast Differentiation Trajectories

The authors sought to investigate whether wound fibroblasts share common differentiation trajectories, given their heterogeneity revealed by t-SNE analysis. In fact, many fibroblasts differentiate into myofibroblasts upon wounding, and contractile markers were detected on scRNA-seq in multiple fibroblast subclusters. Notably, myofibroblasts are the primary progenitors of adipocyte regeneration in large wounds. Pseudotime-based cell ordering revealed a predominant differentiation trajectory among fibroblasts, with two minor bifurcations. RNA velocity analysis was then performed to predict the potential directionality and speed of cell state transitions, considering both spliced and unspliced mRNA counts. This analysis was able to represent cell transitions as vectors, with the length of the vectors reflecting the rate of differentiation. Collectively, the results of pseudo-time and RNA velocity analyses provide a framework for investigating signaling and transcriptional regulators of wound myofibroblast differentiation programs.

Pseudotime analyses reveal putative fibroblast differentiation trajectories.Fig.3 Pseudotime analyses reveal putative fibroblast differentiation trajectories. (Guerrero-Juarez, 2019)

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scRNA-seq.

Single Cell RNA Sequencing Service

Cell populations are rarely homogeneous and synchronized in their characteristics. Single-cell RNA sequencing aims to uncover the transcriptome diversity in heterogeneous samples. Creative Biolabs offers end-to-end workflows including sample preparation, library construction, and data analysis, maximizing your project flexibility, speed, and data accuracy.

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Creative Biolabs offers a comprehensive single cell RNA sequencing service that enables individual cell transcriptome profiling at high throughput. This technology allows us to examine the expression of thousands of genes in individual cells, making it a powerful tool for studying tissue molecular and cellular heterogeneity, identifying rare cell types and subpopulations, and discovering new biomarkers for disease diagnosis and treatment. To provide accurate and reproducible results, our experienced team can assist with experimental design, sample preparation, and data analysis. For any information, please contact us.

Reference

  1. Guerrero-Juarez, C.F.; et al. Single-cell analysis reveals fibroblast heterogeneity and myeloid-derived adipocyte progenitors in murine skin wounds. Nature Communications. 2019, 10: 650.
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