A comparative approach to deciphering the molecular mechanisms of scar-free wound healing

Abstract

Although mammals form scars upon skin wound healing, the Mexican “Axolotl” salamander has the extraordinary ability to heal wounds scar-free. While axolotl skin histologically resembles mammalian skin, molecular details that prevent scar formation during axolotl wound healing are largely unknown. To address this knowledge gap, we performed transcriptional profiling during axolotl cutaneous wound healing. We analyzed genes that displayed differential gene expression during axolotl wound healing compared to previously published human gene expression profiling data. We found that Sal-like 4 (Sall4) expression was increased early during axolotl skin regeneration, but did not increase in humans until later time points. We hypothesize that early increase in expression of SALL4 after injury is required for scar-free wound healing. To test this hypothesis, we depleted SALL4 in vivo during wound healing. We found that when SALL4 is depleted, we see excessive Collagen I and XII deposition that occurs earlier and is not fully remodeled, resulting in a scar-like phenotype. To determine how SALL4 expression is regulated during wound healing, we sought to identify which microRNAs post-transcriptionally regulate SALL4. We found that miR-219 is able to regulate expression of axolotl SALL4 during wound healing. Further, when we ectopically increase miR-219 levels during axolotl wound healing, we find early excessive collagen deposition, mirroring the SALL4 depletion phenotype. Additionally, we found that miR-103, not miR-219, is able to regulate human SALL4. Thus, revealing one mechanism that could explain the different SALL4 expression profiles seen in axolotls vs. humans. Lastly, we describe how to use a Dual-Fluorescent green fluorescent protein (GFP)-Reporter/ monomeric red fluorescent protein (mRFP)- Sensor (DFRS) plasmid to quantitate the dynamics of specific miRNAs over time. This system allows researchers to obtain relative quantifications for microRNA levels during biological processes over time. This will allow researchers explore the expression dynamics of any microRNA over time in vivo.