Human ex vivo wound model and whole-mount staining approach to accurately evaluate skin repair

Wilkinson, Holly Nicola; Kidd, Alexandria Sarah; Roberts, Elizabeth Rose; Hardman, Matthew James

Abstract

© 2021 JoVE Creative Commons. Chronic non-healing wounds, which primarily affect the elderly and diabetic, are a significant area of clinical unmet need. Unfortunately, current chronic wound treatments are inadequate, while available pre-clinical models poorly predict the clinical efficacy of new therapies. Here we describe a high throughput, pre-clinical model to assess multiple aspects of the human skin repair response. Partial thickness wounds were created in human ex vivo skin and cultured across a healing time course. Skin wound biopsies were collected in fixative for the whole-mount staining procedure. Fixed samples were blocked and incubated in primary antibody, with detection achieved via fluorescently conjugated secondary antibody. Wounds were counterstained and imaged via confocal microscopy before calculating percentage wound closure (re-epithelialization) in each biopsy. Applying this protocol, we reveal that 2 mm excisional wounds created in healthy donor skin are fully re-epithelialized by day 4-5 post-wounding. On the contrary, closure rates of diabetic skin wounds are significantly reduced, accompanied by perturbed barrier reformation. Combining human skin wounding with a novel whole-mount staining approach allows a rapid and reproducible method to quantify ex vivo wound repair. Collectively, this protocol provides a valuable human platform to evaluate the effectiveness of potential wound therapies, transforming pre-clinical testing and validation.

Citation

Wilkinson, H. N., Kidd, A. S., Roberts, E. R., & Hardman, M. J. (2021). Human ex vivo wound model and whole-mount staining approach to accurately evaluate skin repair. Journal of visualized experiments : JoVE, 168, Article e62326. https://doi.org/10.3791/62326

• Journal Article Type: Article
• Acceptance Date: Jan 25, 2021
• Online Publication Date: Feb 17, 2021
• Publication Date: 2021
• Deposit Date: May 28, 2021
• Publicly Available Date: May 28, 2021
• Journal: Journal of Visualized Experiments
• Print ISSN: 1940-087X
• Publisher: Journal of Visualized Experiments
• Peer Reviewed: Peer Reviewed
• Volume: 168
• Article Number: e62326
• DOI: https://doi.org/10.3791/62326
• Public URL: https://hull-repository.worktribe.com/output/3742605