International endodontic journal · 2026
Distinct Microbiota and Functional Pathway Profiles Define Success and Failure in Regenerative Endodontic Treatment.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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История · было → стало
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Naorem Leimarembi Devi, Wikström Alina, Quach Peter, Manoharan Lokeshwaran, Ordinola-Zapata Ronald, Rakhimova Olena, Brundin Malin, Vestman Nelly Romani
Аннотация
AIM: To characterize the intracanal microbiota and identify key microbial taxa and functional pathways associated with regenerative endodontic treatment (RET) outcomes.
METHODOLOGY: In this observational cohort study, 196 samples were collected at five time points from external tooth surfaces (T1, T4) and root canals (T2, T3, T5). The V3-V4 hypervariable region of 16S rRNA gene was amplified and sequenced on the Illumina MiSeq platform. Sequence data were pre-processed using QIIME2 and DADA2 to generate amplicon sequence variants (ASVs), classified against the eHOMD database. Microbial diversity, differential abundance, and Receiver Operating Characteristic (ROC) analyses were performed using R statistical software. Functional profiles were predicted using PICRUSt2.
RESULTS: RET induced dynamic shifts in the root canal microbiome, with initially predominant phyla including Actinomycetota, Bacillota, Bacteroidota, Fusobacteriota and Pseudomonadota. Cases with treatment failure consistently showed a higher relative abundance of Fusobacteriota than successful cases. Alpha diversity varied across time points, with outcome-specific differences observed only at T3; beta diversity differed significantly by time point but not by treatment outcome. Differential abundance analysis at T5 revealed enrichment of Rothia dentocariosa and Leptothrix sp. in successful cases, whereas failed cases were enriched in Fusobacterium polymorphum, Streptococcus sanguinis, Campylobacter showae, Lachnoanaerobaculum sp. and Selenomonas sp. These taxa demonstrated moderate diagnostic potential, with area under the curve (AUC) values of 0.70-0.82. Persistence analysis showed that F. polymorphum, C. showae and Selenomonas sp. exhibited greater persistence in failed cases across treatment time points. Predicted functional profiling indicated distinct metabolic potentials between successful and failed treatment groups.
CONCLUSIONS: RET alters the intracanal microbiome, with taxa identified following intracanal dressing exhibiting moderate predictive potential as biomarkers for treatment outcome, thereby contributing to early prognosis and informing RET strategies.
METHODOLOGY: In this observational cohort study, 196 samples were collected at five time points from external tooth surfaces (T1, T4) and root canals (T2, T3, T5). The V3-V4 hypervariable region of 16S rRNA gene was amplified and sequenced on the Illumina MiSeq platform. Sequence data were pre-processed using QIIME2 and DADA2 to generate amplicon sequence variants (ASVs), classified against the eHOMD database. Microbial diversity, differential abundance, and Receiver Operating Characteristic (ROC) analyses were performed using R statistical software. Functional profiles were predicted using PICRUSt2.
RESULTS: RET induced dynamic shifts in the root canal microbiome, with initially predominant phyla including Actinomycetota, Bacillota, Bacteroidota, Fusobacteriota and Pseudomonadota. Cases with treatment failure consistently showed a higher relative abundance of Fusobacteriota than successful cases. Alpha diversity varied across time points, with outcome-specific differences observed only at T3; beta diversity differed significantly by time point but not by treatment outcome. Differential abundance analysis at T5 revealed enrichment of Rothia dentocariosa and Leptothrix sp. in successful cases, whereas failed cases were enriched in Fusobacterium polymorphum, Streptococcus sanguinis, Campylobacter showae, Lachnoanaerobaculum sp. and Selenomonas sp. These taxa demonstrated moderate diagnostic potential, with area under the curve (AUC) values of 0.70-0.82. Persistence analysis showed that F. polymorphum, C. showae and Selenomonas sp. exhibited greater persistence in failed cases across treatment time points. Predicted functional profiling indicated distinct metabolic potentials between successful and failed treatment groups.
CONCLUSIONS: RET alters the intracanal microbiome, with taxa identified following intracanal dressing exhibiting moderate predictive potential as biomarkers for treatment outcome, thereby contributing to early prognosis and informing RET strategies.