Dataset Information

Cutaneous Nod2 Expression Regulates the Skin Microbiome and Wound Healing in a Murine Model.

ABSTRACT: The skin microbiome exists in dynamic equilibrium with the host, but when the skin is compromised, bacteria can colonize the wound and impair wound healing. Thus, the interplay between normal skin microbial interactions versus pathogenic microbial interactions in wound repair is important. Bacteria are recognized by innate host pattern recognition receptors, and we previously showed an important role for the pattern recognition receptor NOD2 in skin wound repair. NOD2 is implicated in changes in the composition of the intestinal microbiota in Crohn's disease, but its role on skin microbiota is unknown. Nod2-deficient (Nod2^-/-) mice had an inherently altered skin microbiome compared with wild-type controls. Furthermore, we found that Nod2^-/- skin microbiome dominated and caused impaired healing, shown in cross-fostering experiments of wild-type pups with Nod2^-/- pups, which then acquired altered cutaneous bacteria and delayed healing. High-throughput sequencing and quantitative real-time PCR showed a significant compositional shift, specifically in the genus Pseudomonas in Nod2^-/- mice. To confirm whether Pseudomonas species directly impair wound healing, wild-type mice were infected with Pseudomonas aeruginosa biofilms and, akin to Nod2^-/- mice, were found to exhibit a significant delay in wound repair. Collectively, these studies show the importance of the microbial communities in skin wound healing outcome.

SUBMITTER: Williams H

PROVIDER: S-EPMC5646944 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundAlthough the sequence of events leading to wound repair has been described at the cellular and, to a limited extent, at the protein level this process has yet to be fully elucidated. Genome wide transcriptional analysis tools promise to further define the global picture of this complex progression of events.Study designThis study was part of a placebo-controlled double-blind clinical trial in which basal cell carcinomas were treated topically with an immunomodifier--toll-like receptor 7 agonist: imiquimod. The fourteen patients with basal cell carcinoma in the placebo arm of the trial received placebo treatment consisting solely of vehicle cream. A skin punch biopsy was obtained immediately before treatment and at the end of the placebo treatment (after 2, 4 or 8 days). 17.5K cDNA microarrays were utilized to profile the biopsy material.ResultsFour gene signatures whose expression changed relative to baseline (before wound induction by the pre-treatment biopsy) were identified. The largest group was comprised predominantly of inflammatory genes whose expression was increased throughout the study. Two additional signatures were observed which included preferentially pro-inflammatory genes in the early post-treatment biopsies (2 days after pre-treatment biopsies) and repair and angiogenesis genes in the later (4 to 8 days) biopsies. The fourth and smallest set of genes was down-regulated throughout the study. Early in wound healing the expression of markers of both M1 and M2 macrophages were increased, but later M2 markers predominated.ConclusionThe initial response to a cutaneous wound induces powerful transcriptional activation of pro-inflammatory stimuli which may alert the host defense. Subsequently and in the absence of infection, inflammation subsides and it is replaced by angiogenesis and remodeling. Understanding this transition which may be driven by a change from a mixed macrophage population to predominantly M2 macrophages, may help the interpretation of the cellular and molecular events occurring in the microenvironment of serially biopsied tissues.

Project description:Wound healing is a well-organized dynamic process involving coordinated consecutive phases: homeostasis, inflammation, proliferation and resolution. Fibroblasts play major roles in skin wound healing such as in wound contraction and release of growth factors which are of importance in angiogenesis and tissue remodeling. Abnormal fibroblast phenotypes have been identified in patients with chronic wounds. In this work, we analyzed scRNA-seq datasets of normal and wounded skin from mice at day 4 post-wound to investigate fibroblast heterogeneity during the proliferative phase of wound healing. Compositional analysis revealed a specific subset of fibroblast (cluster 3) that primarily increased in wounded skin (14%) compared to normal skin (3.9%). This subset was characterized by a gene signature marked by the plasma membrane proteins Sfrp2 + Sfrp4 + Sfrp1 + and the transcription factors Ebf1 + Prrx1 + Maged1 + . Differential gene expression and enrichment analysis identified epithelial to mesenchymal transition (EMT) and angiogenesis to be upregulated in the emerging subset of fibroblasts of the wounded skin. Using two other datasets for murine wounded skin confirmed the increase in cluster 3-like fibroblasts at days 2, 7 and 14 post-wounding with a peak at day 7. By performing a similarity check between the differential gene expression profile between wounded and normal skin for this emerging fibroblast subset with drug signature from the ConnectivityMap database, we identified drugs capable of mimicking the observed gene expression change in fibroblasts during wound healing. TTNPB, verteprofin and nicotinic acid were identified as candidate drugs capable of inducing fibroblast gene expression profile necessary for wound healing. On the other hand, methocarbamol, ifosfamide and penbutolol were recognized to antagonize the identified fibroblast differential expression profile during wound healing which might cause delay in wound healing. Taken together, analysis of murine transcriptomic skin wound healing datasets suggested a subset of fibroblasts capable of inducing EMT and further inferred drugs that might be tested as potential candidates to induce wound closure.

Dataset Information

Cutaneous Nod2 Expression Regulates the Skin Microbiome and Wound Healing in a Murine Model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets