Abstract
BACKGROUND: Diabetic foot osteomyelitis (DFO) is a serious complication of diabetes and a leading cause of lower-limb amputations. Conventional culture-based diagnostics often underestimate the microbial diversity of infected bone tissue. This study represents the first characterization of both total and ribosomally active bone microbiota in Hispanic patients with DFO using high-throughput 16S rRNA gene sequencing. The work aims to contribute to the inclusion of underrepresented populations in microbiome research and informing molecular-based antimicrobial strategies. METHODS: Bone specimens (n = 13) were collected from seven Chilean patients with histologically confirmed DFO. Samples were analyzed using conventional aerobic culture and 16S rRNA gene sequencing from both genomic DNA (gDNA) and complementary DNA (cDNA) to characterize the total bacterial community and the ribosomally active fraction. In three patients, samples were stratified by bone depth (superficial/top, middle and bottom). Microbial diversity and relative abundance were assessed across patients and bone layers. RESULTS: Acute osteomyelitis was the predominant histopathological pattern. Culture yielded 19 bacterial isolates, 95% of which were Gram-negative bacilli. Sequencing identified 3,412 operational taxonomic units (OTUs), with Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria as dominant phyla. Enterobacteriaceae and Enterococcaceae were the most ribosomally active families. Microbial community composition varied substantially among patients and across bone depths. Staphylococcus aureus was infrequent (5% of culture isolates; ~1% of sequence reads), whereas low-abundance but ribosomally active taxa, such as Corynebacteriaceae, were consistently detected across all layers. DISCUSSION: This combined metagenomic and ribosomal transcript analysis reveals a polymicrobial, patient-specific bone microbiota in Chilean patients with DFO, highlighting potentially active bacteria frequently overlooked by standard diagnostic methods. These findings underscore the value of integrating molecular approaches into clinical workflows to improve pathogen detection and support more personalized antimicrobial strategies, while also helping to address gaps in microbiome research among underrepresented populations.