The Early Burn Wound Microbiome, Not Donor-Site Transfer, Marks Graft Healing Outcome.

Authors

Elad Zvi, Carina Chi, Thinh Sieu Tang, Sriya Bobba, Melissa Neely, Roxanne Chatzis, Johannes S Kern, Shiva Akbarzadeh, Céline Pattaroni

Published in

Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society. Volume 34. Issue 5. Pages e70217.

Abstract

Healing after split-skin grafting remains difficult to anticipate in small-area burns, particularly when wounds show no clinically diagnosed infection. We tested whether the burn wound microbiome before grafting captures early wound states linked to subsequent healing. Twenty-six adults with mid-dermal to full-thickness burns involving < 10% total body surface area underwent longitudinal sampling at surgery, graft check and clinic review. At surgery, swabs were collected from the burn wound before grafting, the split-skin donor site and anatomically matched uninjured control skin. Across 170 infection-free samples, microbiome profiling showed that pre-grafting burn wounds already had reduced microbial diversity and distinct community structure compared with matched control skin. This baseline dysbiosis included depletion of commensal-associated anaerobes, including Finegoldia and Anaerococcus and enrichment of opportunistic burn-associated taxa, including Pseudomonas and Acinetobacter. Donor sites acquired a related wound-like microbiome and remodelled in parallel with burn wounds during healing, but post-grafting burn microbiota were not preferentially similar to matched donor sites, arguing against a donor-to-burn microbial transfer. The clearest clinical signal was present before grafting: lower burn wound diversity at surgery was associated with delayed healing, and baseline community structure differed in wounds that later required regrafting. These findings suggest that the pre-grafting burn wound microbiome may provide an early, infection-independent marker of healing trajectory and should be tested as a predictive biomarker in larger prospective cohorts.

PMID:
42856070
Bibliographic data and abstract were imported from PubMed on 10 Oct 2026.

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