Microbial transformation from normal oral microbiota to acute endodontic infections

• Published in: BMC genomics 2012-07, Vol.13 (1), p.345-345, Article 345
• Main Authors: Hsiao, William Wl, Li, Kevin L, Liu, Zhenqiu, Jones, Cheron, Fraser-Liggett, Claire M, Fouad, Ashraf F
• Format: Article
• Language: English
• Subjects: 16S rRNA gene; Acute Disease; Analysis; Analysis of Variance; Bacteria; Bacteria - genetics; Bacterial diversity; Bacterial Infections - microbiology; Biodiversity; Bioinformatics; Confidence Intervals; Dental Pulp Cavity - microbiology; Dental Pulp Cavity - pathology; Development and progression; Disease; DNA, Bacterial - classification; DNA, Bacterial - isolation & purification; Endodontic infection; Endodontic microbiome; Eubacterium; Facial pain; Female; Fusobacterium; Genetic aspects; Genomes; Genomics; Granulicatella adiacens; Health aspects; Health care; Humans; Infection; Infections; Male; Metagenome - genetics; Microbiology; Microbiota (Symbiotic organisms); Molecular Sequence Annotation; Mouth Mucosa - microbiology; Mouth Mucosa - pathology; Next generation sequencing; Oral microbiota; Orofacial pain; Periapical abscess; Periapical Abscess - microbiology; Phylogeny; Physiological aspects; Prevotella; Prevotella melaninogenica; RNA; Root canal therapy; Sequence Analysis, DNA; Software; Species Specificity; Streptococcus; Streptococcus mitis; Studies; Taxonomy; Teeth
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/1471-2164-13-345

Endodontic infections are a leading cause of oro-facial pain and tooth loss in western countries, and may lead to severe life-threatening infections. These infections are polymicrobial with high bacterial diversity. Understanding the spatial transition of microbiota from normal oral cavities through the infected root canal to the acute periapical abscess can improve our knowledge of the pathogenesis of endodontic infections and lead to more effective treatment. We obtained samples from the oral cavity, infected root canal and periapical abscess of 8 patients (5 with localized and 3 with systemic infections). Microbial populations in these samples were analyzed using next-generation sequencing of 16S rRNA amplicons. Bioinformatics tools and statistical tests with rigorous criteria were used to elucidate the spatial transition of the microbiota from normal to diseased sites. On average, 10,000 partial 16S rRNA gene sequences were obtained from each sample. All sequences fell into 11 different bacterial phyla. The microbial diversity in root canal and abscess samples was significantly lower than in the oral samples. Streptococcus was the most abundant genus in oral cavities while Prevotella and Fusobacterium were most abundant in diseased samples. The microbiota community structures of root canal and abscess samples were, however, more similar to each other than to the oral cavity microbiota. Using rigorous criteria and novel bioinformatics tools, we found that Granulicatella adiacens, Eubacterium yurii, Prevotella melaninogenica, Prevotella salivae, Streptococcus mitis, and Atopobium rimae were over-represented in diseased samples. We used a novel approach and high-throughput methodologies to characterize the microbiota associated normal and diseased oral sites in the same individuals.