The ecological diversity of the periodontal microenvironment may provide suitable conditions for the colonization of species not usually considered members of the oral microbiota. In this investigation, we aimed to determine the prevalence and levels of pathogenic species of medical relevance in the microbiota of individuals with distinct periodontal clinical status. Subgingival biofilm was obtained from patients with periodontal health (H, n = 81), gingivitis (G, n = 55), generalized aggressive (AgP, n = 36) or chronic periodontitis (CP, n = 98), and analyzed for 39 microbial taxa using a checkerboard DNA-DNA hybridization technique. Microbial differences among groups, as well as associations between clinical and microbiological parameters were sought by non-parametric and univariate correlation tests. Neisseria spp., Peptostreptococus anaerobius, Candida albicans, enterobacteria, Pseudomonas aeruginosa, Eubacterium saphenum, Clostridium difficile and Olsenella uli were detected in high mean prevalence and counts in the subgingival microbiota of the study population. Species that were more related to periodontal inflammation and tissue destruction at the patient and site levels included enterobacteria, C. albicans, Neisseria spp., P. aeruginosa, O. uli, Hafnia alvei, Serratia marcescens and Filifactor alocis (p < 0.05). In contrast, Fusobacterium necrophorum, Lactobacillus acidophilus, Staphylococcus aureus and Streptococcus pneumoniae were associated with periodontal health (p < 0.05). Pathogenic species of medical importance may be detected in high prevalence and levels in the periodontal microbiota. Regardless of their role in periodontal health or disease, the periodontal biofilm may be a source for dissemination and development of systemic infections by these pathogenic microorganisms.

Aim: To determine microbial profiles that discriminate periodontal health from different forms of periodontal diseases. Methods: Subgingival biofilm was obtained from patients with periodontal health (27), gingivitis (11), chronic periodontitis (35) and aggressive periodontitis (24), and analysed for the presence of >250 species/phylotypes using HOMIM. Microbial differences among groups were examined by Mann-Whitney U-test. Regression analyses were performed to determine microbial risk indicators of disease. Conclusion: There were specific microbial signatures of the subgingival biofilm that were able to distinguish between microbiomes of periodontal health and diseases. Such profiles may be used to establish risk of disease.

Putative periodontal pathogens and non-oral bacteria alone or in association were strongly associated with periodontitis.

AimTo quantify the proteome composition of the GCF in periodontal health (HH) and in sites with different clinical conditions in chronic periodontitis (CP) subjects.Material and Methods5 subjects with HH and 5 with CP were submitted to full-mouth periodontal examination, and GCF sampling. Sites in the CP group were classified and sampled as periodontitis (P, probing depth, PD>4 mm), gingivitis (G, PD≤3mm with bleeding on probing, BOP), and healthy sites (H, PD≤3mm without BOP). GCF proteins were subjected to liquid chromatography electrospray ionization mass spectrometry for identification, characterization and quantification.Results230 proteins were identified; 145 proteins were detected in HH, 214 in P, 154 in G, and 133 in H. Four proteins were exclusively detected at HH, 43 proteins at P, 7 proteins at G, and 1 protein at H. Compared to HH group, 35 and 6 proteins were more abundant in P and G (p<0.001), respectively; and 4, 15 and 37 proteins were less abundant in P, G and H (p≤0.01), respectively.ConclusionsThere are marked differences in the GCF proteome according to disease profile. Comprehension of the role of the identified proteins in the etiopathogenesis of periodontal disease may lead to biomarkers definition.