Identification of a myofibroblast-specific expression signature in skin wounds

After skin injury fibroblasts migrate into the wound and transform into contractile extracellular matrix-producing myofibroblasts to promote skin repair. Persistent activation of myofibroblasts can cause excessive fibrotic reactions, but the underlying mechanisms are not fully understood. We used SMA-GFP transgenic mice to study myofibroblast recruitment and activation in skin wounds. Myofibroblasts were initially recruited to wounds three days post injury reached a maximum after seven days and subsequently declined. Expression profiling showed that 1749 genes were differentially expressed in sorted myofibroblasts from wounds seven days post injury. GO-Term analysis associated most of these genes with the extracellular region and cell periphery including upregulated genes encoding for ECM proteins, integrins and focal adhesion proteins and a specific set of growth factors, cytokines and chemokines promoting the healing response. In contrast, cell adhesion molecules involved in cell-cell interaction were downregulated. Novel genes not yet known to be expressed in myofibroblast were found. Hence, this first characterization of a myofibroblast specific expression network at the peak of granulation tissue formation in situ provides important insights into myofibroblast activation in skin wounds and identifies novel target genes to control excessive ECM deposition during fibrotic reactions. Non-hematopoietic (CD45-)/non-endothelial (CD31-) cell populations with low expression of SMA-GFP from dermis (SMA-GFP+) and with high expression from wounds 7 days post injury (SMA-GFP+++) were isolated by cell sorting from transgenic SMA-GFP mice. Total RNA of was isolated with TRIZOL (Life Technologies) and RNA quality was confirmed using micro capillary electrophoresis (2100 Bioanalyzer, Agilent). ~50ng of RNA was amplified, labeled and hybridized to Sureprint G3 human GE 8x60K or whole genome mRNA microarray according to the manufacturer’s specifications (Low input Quick Amp Labeling kit, Agilent). The arrays were scanned (Agilent G2595C scanner), data extracted and processed to create a generic gene level experiments from two technologies using the Genespring 14.5 software (Agilent).