bioRxivMicrobiologyPreprint
What is Slough?A pilot study to define the proteomic and microbial composition of wound slough and its implications for wound healing.
E. Townsend, J. A. Cheong, M. Razieta, B. G. Fritz, T. Bjarnsholt, M. Malone, K. Ousey, T. Swanson, G. Schultz, A. Gibson, L. Kalan
Abstract
Slough is a well-known feature of non-healing wounds. This study aims to determine the proteomic and microbiologic components of slough as well as interrogate the associations between wound slough components and wound healing. Twenty-three subjects with slow-to-heal wounds and visible slough were enrolled. Etiologies included venous stasis ulcers, post-surgical site infections, and pressure ulcers. Patient co-morbidities and wound healing outcome at 3-months post-sample collection was recorded. Debrided slough was analyzed microscopically, through untargeted proteomics, and high-throughput bacterial 16S-ribosomal gene sequencing. Microscopic imaging revealed wound slough to be amorphous in structure and highly variable. 16S-profiling found slough microbial communities to associate with wound etiology and location on the body. Across all subjects, slough largely consisted of proteins involved in skin structure and formation, blood-clot formation, and immune processes. To predict variables associated with wound healing, protein, microbial, and clinical datasets were integrated into a supervised discriminant analysis. This analysis revealed that healing wounds were enriched for proteins involved in skin barrier development and negative regulation of immune responses. While wounds that deteriorated over time started off with a higher baseline Bates-Jensen Wound Assessment Score and were enriched for anerobic bacterial taxa and chronic inflammatory proteins. To our knowledge, this is the first study to integrate clinical, microbiome, and proteomic data to systematically characterize wound slough and integrate it into a single assessment to predict wound healing outcome. Collectively, our findings underscore how slough components can help identify wounds at risk of continued impaired healing and serves as an underutilized biomarker.
- organism: human
- assay: proteomics
- assay: metagenomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
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