A Murine Model of a Burn Wound Reconstructed with an Allogeneic Skin Graft

J Vis Exp. 2020 Aug 8:(162). doi: 10.3791/61339.

Abstract

Trivial superficial wounds heal without complications by primary intention. Deep wounds, such as full thickness burns, heal by secondary intention and require surgical debridement and skin grafting. Successful integration of the donor graft into a recipient wound bed depends on timely recruitment of immune cells, robust angiogenic response and new extracellular matrix formation. The development of novel therapeutic agents, which target some key processes involved in wound healing, are hindered by the lack of reliable preclinical models with optimized objective assessment of wound closure. Here, we describe an inexpensive and reproducible model of experimental full thickness burn wound reconstructed with an allogeneic skin graft. The wound is induced on the dorsum surface of anaesthetized inbred wild type mice from the BALB/C and SKH1-Hrhr backgrounds. The burn is produced using a brass template measuring 10 mm in diameter, which is preheated to 80 °C and delivered at a constant pressure for 20 s. Burn eschar is excised 24 hours after the injury and replaced with a full thickness graft harvested from the tail of a genetically similar donor mouse. No specialized equipment is required for the procedure and surgical techniques are straightforward to follow. The method may be effortlessly implemented and reproduced in most research settings. Certain limitations are associated with the model. Due to technical difficulties, the harvest of thinner split thickness skin grafts is not possible. The surgical method we describe here allows for the reconstruction of burn wounds using full thickness skin grafts. It may be used to carry out preclinical therapeutic testing.

Publication types

  • Research Support, Non-U.S. Gov't
  • Video-Audio Media

MeSH terms

  • Allografts
  • Animals
  • Burns / pathology*
  • Disease Models, Animal*
  • Mice
  • Mice, Inbred BALB C
  • Skin Transplantation* / methods