Longitudinal study identifies microbial signatures predicting bone regeneration in odontogenic lesions, suggesting new management approaches.
Background Marsupialization is a conservative treatment for odontogenic jaw lesions but is hampered by protracted, unpredictable bone regeneration, lacking early biomarkers. Furthermore, whether these intraosseous lesions harbour a unique microbiome remains unknown. We aimed to characterize microbial dynamics during treatment and develop a prognostic model to address clinical unpredictability.Methods A prospective longitudinal study was conducted with multi-site sampling (saliva, tissue, luminal fluid and swabs) across three phases: primary surgery, 3-month follow-up and secondary surgery. Bacterial 16S rRNA gene sequencing was subsequently performed. Microbial dynamics were analyzed using diversity analysis and source tracking. A prognostic model was constructed using a hybrid feature selection strategy to predict 12-month bone regeneration using 3-month post-operative swabs.Results Baseline analysis revealed that odontogenic jaw lesions harbour a unique, biologically selected microbiome enriched in Fusobacterium and Clostridia, which are distinct from saliva. Marsupialization induced a profound microbial remodelling, transforming this closed niche into an open, stochastic ecosystem dominated by salivary commensals. Long-term analysis indicated a secondary succession, where primary pathogens were replaced by a Bacteroidia-enriched community. Crucially, after a rigorous feature selection process, a streamlined microbial signature accurately predicted 12-month bone regeneration (AUC = 0.937). Poor bone regeneration was associated with the persistence of the primary Clostridia core, whereas favourable regeneration was linked to a shift towards Bacteroidia and Proteobacteria.Conclusion Marsupialization drives the lesion microbiome from a pathogenic niche toward a stochastic, commensal-like state. This succession trajectory is associated with clinical outcome. Our prognostic model offers a novel precision tool to optimize lesion management.
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Zeng et al. (2026) studied this question.
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