Periodontal disease (PD) is a common dental disease associated with the interaction between dysbiotic oral microbiota and host immunity. It is a prevalent disease, resulting in loss of gingival tissue, periodontal ligament, cementum and alveolar bone. PD is a major form of tooth loss in the adult population. Experimental animal models have enabled the study of PD pathogenesis and are used to test new therapeutic approaches for treating the disease. The ligature-induced periodontitis model has several advantages as compared with other models, including rapid disease induction, predictable bone loss and the capacity to study periodontal tissue and alveolar bone regeneration because the model is established within the periodontal apparatus. Although mice are the most convenient and versatile animal models used in research, ligature-induced periodontitis has been more frequently used in large animals. This is mostly due to the technical challenges involved in consistently placing ligatures around murine teeth. To reduce the technical challenge associated with the traditional ligature model, we previously developed a simplified method to easily install a bacterially retentive ligature between two molars for inducing periodontitis. In this protocol, we provide detailed instructions for placement of the ligature and demonstrate how the model can be used to evaluate gingival tissue inflammation and alveolar bone loss over a period of 18 d after ligature placement. This model can also be used on germ-free mice to investigate the role of human oral bacteria in periodontitis in vivo. In conclusion, this protocol enables the mechanistic study of the pathogenesis of periodontitis in vivo.

Inflammasomes are a group of multimolecular intracellular complexes assembled around several innate immune proteins. Recognition of a diverse range of microbial, stress and damage signals by inflammasomes results in direct activation of caspase‐1, which subsequently induces the only known form of secretion of active interleukin‐1β and interleukin‐18. Although the importance of interleukin‐1β in the periodontium is not questioned, the impact of inflammasomes in periodontal disease and its potential for therapeutics in periodontology is still in its very early stages. Increasing evidence in preclinical models and human data strongly implicate the involvement of inflammasomes in a number of inflammatory, autoinflammatory and autoimmune disorders. Here we review: (a) the currently known inflammasome functions, (b) clinical/preclinical data supporting inflammasome involvement in the context of periodontal and comorbid diseases and (c) potential therapies targeting inflammasomes. To clarify further the inflammasome involvement in periodontitis, we present analyses of data from a large clinical study (n = 5809) that measured the gingival crevicular fluid‐interleukin‐1β and grouped the participants based on current periodontal disease classifications. We review data on 4910 European‐Americans that correlate 16 polymorphisms in the interleukin‐1B region with high gingival crevicular fluid‐interleukin‐1β levels. We show that inflammasome components are increased in diseased periodontal tissues and that the caspase‐1 inhibitor, VX‐765, inhibits ~50% of alveolar bone loss in experimental periodontitis. The literature review further supports that although patients clinically present with the same phenotype, the disease that develops probably has different underlying biological pathways. The current data indicate that inflammasomes have a role in periodontal disease pathogenesis. Understanding the contribution of different inflammasomes to disease development and distinct patient susceptibility will probably translate into improved, personalized therapies.

Emerging evidence suggests comprehensive immune profiling represents a highly promising, yet insufficiently tapped approach to identify potentially prognostic signatures for periodontitis. In this report, we agnostically identified a periodontitis-associated inflammatory expression network with multiple biomarkers identified within gingival crevicular fluid samples from study participants by applying principal component analysis. We identified an IL-17-dominated trait that is associated with periodontal disease and is inversely modified by the level of IL-10. IL-10 mitigated chemokine CXCL5 and CXCL1 expressions in IL-17-stimulated peripheral blood monocytic cells and peripheral blood monocytic cell-derived macrophages. Il10-deficient mice presented more bone loss, which was associated with more Il17 and IL-17-mediated chemokine and cytokine expression at the transcriptional levels in comparison with control wild-type mice in both the Porphyromonas gingivalis-induced experimental murine periodontitis and ligature-induced alveolar bone-loss models. The dampening effect of IL-10 on the excessive signaling of IL-17 appeared to be mediated by innate immune cells populations rather than by gingival epithelial cells, which are the major cell target for IL-17 signaling. Additionally, elevated IL-17 response in Il10-deficient mice specifically elicited an M1-skewing macrophage phenotype in the gingiva that was associated with the advanced bone loss in the ligature model. In summary, IL-17 dominated an inflammatory network characteristic of periodontitis, and IL-10 dampens this excessive IL-17-mediated periodontitis trait.

Objectives We have previously characterized the main osteoimmunological events that occur during ligature periodontitis. This study aims to determine the polymicrobial community shifts that occur during disease development. Methods Periodontitis was induced in C57BL/6 mice using the ligature‐induced periodontitis model. Healthy oral mucosa swabs and ligatures were collected every 3 days from 0 to 18 days post‐ligature placement. Biofilm samples were evaluated by 16SrRNA gene sequencing (Illumina MiSeq) and QIIME. Time‐course changes were determined by relative abundance, diversity, and rank analyses (PERMANOVA, Bonferroni‐adjusted). Results Microbial differences between health and periodontal inflammation were observed at all phylogenic levels. An evident microbial community shift occurred in 25 genera during the advancement of “gingivitis” (3–6 days) to periodontitis (9–18 days). From day 0 to 18, dramatic changes were identified in Streptococcus levels, with an overall decrease (54.04%–0.02%) as well an overall increase of Enterococcus and Lactobacillus (23.7%–73.1% and 10.1%–70.2%, respectively). Alpha‐diversity decreased to its lowest at 3 days, followed by an increase in diversity as disease advancement. Beta‐diversity increased after ligature placement, indicating that bone loss develops in response to a greater microbial variability (p = 0.001). Levels of facultative and strict anaerobic bacteria augmented over the course of disease progression, with a total of eight species significantly different during the 18‐day period. Conclusion The data supports that murine gingival inflammation and alveolar bone loss develop in response to microbiome shifts. Bacterial diversity increased during progression to bone loss. These findings further support the utilization of the periodontitis ligature model for microbial shift analysis under different experimental conditions.

Background: Periodontal destruction can be the result of different known and yet-to-be-discovered biological pathways. Recent human genetic association studies have implicated interferon-gamma inducible protein 16 (IFI16) and absent in melanoma 2 (AIM2) with high periodontal interleukin (IL)-1β levels and more destructive disease, but mechanistic evidence is lacking. Here, we sought to experimentally validate these observational associations and better understand IFI16 and AIM2's roles in periodontitis.Methods: Periodontitis was induced in Ifi204 -/-(IFI16 murine homolog) and Aim2 -/mice using the ligature model. Chimeric mice were created to identify the main source cells of Ifi204 in the periodontium. IFI16-silenced human endothelial cells were treated with periodontal pathogens in vitro. Periodontal tissues from Ifi204 -/mice were evaluated for alveolar bone (micro-CT), cell inflammatory infiltration (MPO+ staining), Il1b (qRT-PCR), and osteoclast numbers (cathepsin K+ staining).