Periodontal pathogens and clinical parameters in chronic periodontitis.

The use of next generation sequencing and bioinformatics has revealed the complexity and richness of the human oral microbiota. While some species are well known for their periodontal pathogenicity, the molecular-based approaches for bacterial identification have raised awareness about new putative periodontal pathogens. Although they are found increased in case of periodontitis, there is currently a lack of data on their interrelationship with the periodontal measures. We processed the sequencing data of the subgingival microbiota of 75 patients with hemochromatosis and chronic periodontitis in order to characterize the well-described and newly identified subgingival periodontal pathogens. We used correlation tests and statistical models to assess the association between the periodontal pathogens and mean pocket depth, and to determine the most relevant bacterial biomarkers of periodontitis severity. Based on correlation test results, nine taxa were selected and included in the statistical models. The multiple linear regression models adjusted for systemic and periodontal clinical variables showed that mean pocket depth was negatively associated with Aggregatibacter and Rothia, and positively associated with Porphyromonas. Furthermore, a bacterial ratio that was previously described as a signature of dysbiosis in periodontitis (%Porphyromonas+%Treponema+%Tannerella)/(%Rothia+%Corynebacterium) was the most significant predictor. In this specific population, we found that the best model in predicting the mean pocket depth was microbial dysbiosis using the dysbiosis ratio taxa formula. While further studies are needed to assess the validity of these results on the general population, such a dysbiosis ratio could be used in the future to monitor the subgingival microbiota.

Unprimed, M1 and M2 Macrophages Differentially Interact with Porphyromonas gingivalis.

Porphyromonas gingivalis is a keystone pathogen in the development of chronic periodontitis. Tissue macrophages are amongst the first immune cells to respond to bacteria and depending on the cytokine profile at the infection site, macrophages are primed to react to infection in different ways. Priming of naive macrophages with IFN-γ produces a classical pro-inflammatory, antibacterial M1 macrophage after TLR ligation, whereas priming with IL-4 induces an anti-inflammatory tissue-repair M2 phenotype. Previous work has shown that M1 are preferentially generated in gingival tissue following infection with P. gingivalis. However, few studies have investigated the interactions of macrophage subsets with P. gingivalis cells. The aim of this study was to determine the ability of naive, M1 and M2 macrophages to phagocytose P. gingivalis and investigate how this interaction affects both the bacterial cell and the macrophage. M1 and M2 macrophages were both found to have enhanced phagocytic capacity compared with that of naive macrophages, however only the naive and M1 macrophages were able to produce a respiratory burst in order to clear the bacteria from the phagosome. P. gingivalis was found to persist in naive and M2, but not M1 macrophages for 24 hours. Phagocytosis of P. gingivalis also induced high levels of TNF-α, IL-12 and iNOS in M1 macrophages, but not in naive or M2 macrophages. Furthermore, infection of macrophages with P. gingivalis at high bacteria to macrophage ratios, while inducing an inflammatory response, was also found to be deleterious to macrophage longevity, with high levels of apoptotic cell death found in macrophages after infection. The activation of M1 macrophages observed in this study may contribute to the initiation and maintenance of a pro-inflammatory state during chronic periodontitis.