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Background  Infected diabetic foot ulcers (IDFU) are a major complication of diabetes mellitus. These potentially limb-threatening ulcers are challenging to treat due to impaired wound healing characterizing diabetic patients and the complex microbial environment of these ulcers.    Aim  To analyze the microbiome of IDFU in association with clinical outcomes.    Methods  Wound biopsies from IDFU were obtained from hospitalized patients and were analyzed using traditional microbiology cultures, 16S rRNA sequencing and metagenomic sequencing. Patients’ characteristics, culture-based results and sequencing data were analyzed in association with clinical outcomes.    Results  A total of 31 patients were enrolled. Gram-negative bacteria dominated the IDFU samples (79%, 59% and 54% of metagenomics, 16S rRNA and cultures results, respectively, p&amp;lt;0.001). 16S rRNA and metagenomic sequencing detected significantly more anaerobic bacteria, as compared to conventional cultures (59% and 76%, respectively vs. 26% in cultures, p=0.001). Culture-based results showed that  Staphylococcus aureus  was more prevalent among patients who were treated conservatively (p=0.048). In metagenomic analysis, the  Bacteroides  genus was more prevalent among patients who underwent amputation (p&amp;lt;0.001). Analysis of metagenomic-based functional data showed that antibiotic resistance genes and genes related to biofilm production and to bacterial virulent factors were more prevalent in IDFU that resulted in amputation (p&amp;lt;0.001).    Conclusion  Sequencing tools uncover the complex biodiversity of IDFU and emphasize the high prevalence of anaerobes and Gram-negative bacteria in these ulcers. Furthermore, sequencing results highlight possible associations among certain genera, species, and bacterial functional genes to clinical outcomes.

frontiers in cellular and infection microbiology

Microbiome Characterization of Infected Diabetic Foot Ulcers in Association With Clinical Outcomes: Traditional Cultures Versus Molecular Sequencing Methods