A Microbiome And Metabolomic Signature Of Phases Of Cutaneous Healing Identified By Profiling Sequential Acute Wounds Of Human Skin
Mohammed Ashrafi, Yun Xu, Howbeer Muhamadali, Iain White, Max Wilkinson, Katherine Holloywood, Mohamed Baguneid, Royston Goodacre, Ardeshir Bayat.
The University of Manchester, Manchester, United Kingdom.
BACKGROUND - Profiling skin microbiome and metabolome has been utilised to gain further insight into wound healing processes, although knowledge of the metabolic profile of wounds and their role in wound healing processes is limited. The aims of this multi-part temporal study in 11 volunteers were to analytically profile the dynamic wound tissue and headspace metabolome and sequence microbial communities in acute wound healing at days 0, 7, 14, 21 and 28, and to investigate their relationship to wound healing, using non-invasive quantitative devices.
METHODS - Subjects had four 5-mm diameter skin biopsies to their arms. Metabolites were obtained using tissue extraction, sorbent and polydimethylsiloxane patches and underwent thermal desorption and were then separated by gas chromatography and detected by mass spectrometry. Metabolites were tentatively identified using the National Institute of Standards and Technology and Golm libraries. Participants wound tissue samples underwent DNA extraction and 16S rDNA sequencing. Spectrophotometric intracutaneous analysis, full-field laser perfusion imaging, Dermalab system and dynamic optical coherence tomography provided non-invasive quantitative measurements of melanin, haemoglobin, collagen, blood flow, transepidermal water loss, hydration and erythema.
RESULTS - Principal component analysis of wound tissue metabolome clearly separated time points with 10 metabolites of 346 being involved in separation. Analysis of variance-simultaneous component analysis identified a difference between the wound headspace metabolome, sites (P=0.0024) and time points (P<0.0001), with 10 metabolites of 129 measured were associated with separation between sites and time points. A reciprocal relationship between Staphylococcus spp. and Propionibacterium spp. was observed at day 21 (P<0.05) with a correlation between collagen and Propionibacterium (r=0.417; P=0.038) and Staphylococcus (r=-0.434; P=0.03). Procrustes analysis showed a significant similarity between wound headspace and tissue metabolome with non-invasive wound devices.
CONCLUSIONS - This study demonstrates the temporal and dynamic nature of acute wound metabolome and microbiome presenting a novel class of biomarkers that correspond to wound healing.
Back to 2019 Abstracts