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

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.

Keywords: bone biopsy; diabetic foot osteomyelitis; metagenomics next‐generation sequencing; microbial diversity; osteomyelitis management.