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. 2016 Sep 6;7(5):e01058-16.
doi: 10.1128/mBio.01058-16.

Redefining the Chronic-Wound Microbiome: Fungal Communities Are Prevalent, Dynamic, and Associated with Delayed Healing

Lindsay Kalan  1 , Michael Loesche  1 , Brendan P Hodkinson  1 , Kristopher Heilmann  2 , Gordon Ruthel  3 , Sue E Gardner  4 , Elizabeth A Grice  5
Affiliations

Redefining the Chronic-Wound Microbiome: Fungal Communities Are Prevalent, Dynamic, and Associated with Delayed Healing

"V体育ios版" Lindsay Kalan et al. mBio. .

Abstract

Chronic nonhealing wounds have been heralded as a silent epidemic, causing significant morbidity and mortality especially in elderly, diabetic, and obese populations. Polymicrobial biofilms in the wound bed are hypothesized to disrupt the highly coordinated and sequential events of cutaneous healing. Both culture-dependent and -independent studies of the chronic-wound microbiome have almost exclusively focused on bacteria, omitting what we hypothesize are important fungal contributions to impaired healing and the development of complications. Here we show for the first time that fungal communities (the mycobiome) in chronic wounds are predictive of healing time, associated with poor outcomes, and form mixed fungal-bacterial biofilms. We longitudinally profiled 100, nonhealing diabetic-foot ulcers with high-throughput sequencing of the pan-fungal internal transcribed spacer 1 (ITS1) locus, estimating that up to 80% of wounds contain fungi, whereas cultures performed in parallel captured only 5% of colonized wounds. The "mycobiome" was highly heterogeneous over time and between subjects. Fungal diversity increased with antibiotic administration and onset of a clinical complication. The proportions of the phylum Ascomycota were significantly greater (P = 0. 015) at the beginning of the study in wounds that took >8 weeks to heal. Wound necrosis was distinctly associated with pathogenic fungal species, while taxa identified as allergenic filamentous fungi were associated with low levels of systemic inflammation. Directed culturing of wounds stably colonized by pathogens revealed that interkingdom biofilms formed between yeasts and coisolated bacteria. Combined, our analyses provide enhanced resolution of the mycobiome during impaired wound healing, its role in chronic disease, and impact on clinical outcomes VSports手机版. .

Importance: Wounds are an underappreciated but serious complication for a diverse spectrum of diseases. High-risk groups, such as persons with diabetes, have a 25% lifetime risk of developing a wound that can become chronic. The majority of microbiome research related to chronic wounds is focused on bacteria, but the association of fungi with clinical outcomes remains to be elucidated. Here we describe the dynamic fungal communities in 100 diabetic patients with foot ulcers. We found that communities are unstable over time, but at the first clinical presentation, the relative proportions of different phyla predict healing times V体育安卓版. Pathogenic fungi not identified by culture reside in necrotic wounds and are associated with a poor prognosis. In wounds stably colonized by fungi, we identified yeasts capable of forming biofilms in concert with bacteria. Our findings illuminate the associations of the fungal mycobiome with wound prognosis and healing. .

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Figures

FIG 1
FIG 1
The DFU mycobiome is diverse and highly heterogeneous. (A) Heatmap of fungal community structure for all subjects at the baseline study visit. Hierarchical clustering was performed for taxa found in >20% abundance in at least one specimen. (B) Boxplot showing the Shannon diversity index (y axis) by wound location (x axis). P values were calculated by pairwise Wilcoxon rank sum test and adjusted for multiple comparison by the method of Holm. (C) Relative abundance plot showing the mean proportions of taxa found in >1% abundance in all of the samples (y axis) by wound location (x axis). Taxa found in significantly different abundance in the forefoot and hind foot wounds are listed in Table S2 in the supplemental material. (D) Boxplot showing the weighted UniFrac distances (y axis) between subjects (baseline study visit only) and within subjects longitudinally (x axis). The P value was calculated by Wilcoxon rank sum test. Notches in boxplots display the 95% confidence interval around the median.
FIG 2
FIG 2
The DFU mycobiome is temporally unstable. Five individual subject timelines showing the relative abundance and structure of fungal communities for DFUs that healed (subjects 145, 117, 159), that did not heal within the 26 weeks of the study (subject 186), or that resulted in an amputation (subject 198). The numbers on the x axis are the study visit numbers, and the y axis represents proportion of taxa present.
FIG 3
FIG 3
The DFU mycobiome is associated with clinical outcomes. (A) Relative distribution of Ascomycota and Basidiomycota in specimens grouped by time (in weeks) to heal. Baseline specimens (BS) (left panel) were taken from viable wound tissue prior to sharp debridement and cleansing. All study visits after the baseline study visit are combined (Post) (right panel). P values are calculated with an analysis of variance model and post-hoc Tukey honest significant difference (HSD) multiple comparison of means. NS, not significant. (B) A boxplot showing intervisit weighted UniFrac distances (y axis) by end of study outcome (x axis) were not significantly different. Notches display the 95% confidence interval around the median. (C) A timeline of weighted UniFrac distances (y axis) plotted by study visit (x axis) for individual subjects and grouped by end of study outcome (healed, unhealed after 26 weeks of follow-up, and amputation). Blue dots indicate that a complication was recorded at the study visit. Triangles indicate a study visit at which an antibiotic was administered at or within the previous 2 weeks.
FIG 4
FIG 4
Pathogens are associated with necrotic tissue and poor outcomes. (A) Mean proportion (shown as a percentage) (x axis) of pathogen (y axis) and allergen (y axis) taxa in the data set. (B) Mean proportion of pathogens (y axis) by end of study outcome (x axis). Error bars indicate standard errors of the means. (C) Mean proportion of pathogens, allergens, unclassified fungi, and unclassified Ascomycota in samples grouped by the level of necrotic tissue present in the wound. The level of pathogens is significantly higher in ulcers with >75% necrotic tissue compared to all other levels of necrosis. P values are calculated with an analysis of variance model and post-hoc Tukey HSD multiple comparison of means. (D) Principal-coordinate plot comparing samples by the weighted UniFrac distance. Percent variation explained by each principal coordinate (PC) is indicated by the percentage next to each axis. Point size indicates necrotic tissue level, with larger points corresponding to greater amounts of necrotic tissue in the wound from which the specimen was taken. The proportions of allergens and pathogens were calculated by subtracting the proportion of pathogens from the proportion of allergens in each sample resulting in a scale of −1 (dominated by pathogens) to +1 (dominated by allergens). A value of zero indicates either zero or equal proportions of each.
FIG 5
FIG 5
Pathogens form interkingdom biofilms. Fluorescent confocal microscope images of mono- or coculture Candida albicans and Citrobacter freundii or Trichosporon asahii and Staphylococcus simulans. Biofilms were grown for 48 h at 37°C on polystyrene plates in RPMI 1640 medium with GlutaMAX supplement, washed to remove planktonic cells, and stained with SYTO 9 and hexidium iodide (HI) prior to imaging. Fungi (large) and bacteria (small) can be distinguished by size. Fungi appear green and bacteria appear red in the merged images. The size of the scale bar for each row is labeled in the first column (SYTO 9) for each culture. The insets are zoomed-in portions of the merged coculture biofilm images.
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