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February 19, 2026Diabetic Medicine0 citations

Enhancing diabetic foot osteomyelitis diagnosis with metagenomics next‐generation sequencing, proof of concept

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MMMadjid MorsliCMChloé MagnanFSFlorian Salipante

Key Points

  • The study aims to evaluate the effectiveness of metagenomics next-generation sequencing (mNGS) in diagnosing diabetic foot osteomyelitis (DFOM).
  • Retrospective analysis of ten bone biopsies from nine diabetic individuals
  • Comparison of routine microbiological culture and metagenomics next-generation sequencing (mNGS)
  • Assessment of microbial diversity using the Shannon index
  • Identification of resistance genes via mNGS
  • Routine culture identified 11 bacterial species in seven biopsies; mNGS detected 84 species
  • High microbial diversity correlated with severe osteomyelitis cases leading to amputation
  • One culture-negative biopsy revealed significant bacterial diversity via mNGS, leading to a severe infection within days
  • mNGS identified resistance genes, aiding in targeted therapy for infections

Abstract

Abstract Diabetic foot osteomyelitis (DFOM) is a serious medical condition that necessitates robust diagnostic tools for effective clinical management. Conventional diagnostic methods for DFOM rely heavily on bacterial culture, which is time‐consuming and may fail to capture the full microbial diversity present in infections. This pilot study explored the utility of metagenomics next‐generation sequencing (mNGS) as a complementary diagnostic tool for DFOM. We retrospectively analysed ten bone biopsies from nine diabetic persons using both routine microbiological culture and mNGS. Routine culture identified 11 bacterial species across seven biopsies, while mNGS detected 84 species, including all those found by culture. High microbial diversity (Shannon index = 1.10) was associated with severe osteomyelitis, leading to amputation in three of seven DFOM cases. Interestingly, one culture‐negative biopsy revealed high bacterial diversity by mNGS and progressed to a severe infection within 7 days. mNGS also identified resistance genes, providing additional insights for targeted therapy. Integrating mNGS into routine clinical microbiology may serve as a complementary method to conventional diagnostics, particularly for distinguishing infection from colonization and predicting clinical outcomes. However, challenges such as human DNA contamination and limited sequencing depth must be addressed to optimize its clinical application. These findings support the integration of mNGS into diagnostic workflows for bone biopsies for improved management of DFOM.

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Cite This Study

Morsli et al. (2026) studied this question.

synapsesocial.com/papers/6996a7e3ecb39a600b3edf67https://doi.org/10.1111/dme.70235
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