Periodontal inflammation: Integrating genes and dysbiosis

Abstract

Biofilm bacteria co-evolve and reach a symbiosis with the host on the gingival surface. The disruption of the homeostatic relationship between plaque bacteria and the host can initiate and promote periodontal disease progression. Recent advances in sequencing technologies allow researchers to profile disease-associated microbial communities and quantify microbial metabolic activities and host transcriptional responses. In addition to confirming the findings from previous studies, new putative pathogens and novel genes that have not previously been associated with periodontitis, emerge. For example, multiple studies have reported that Synergistetes bacteria are associated with periodontitis. Genes involved in epithelial barrier defense were downregulated in periodontitis, while excessive expression of interleukin-17 was associated with a hyperinflammatory response in periodontitis and with a unique microbial community. Bioinformatics-enabled gene ontology pathway analyses provide a panoramic view of the bacterial and host activities as they shift from periodontal health to disease. Additionally, host innate factors, such as genetic variants identified by either a candidate-gene approach or genome-wide association analyses, have an impact on subgingival bacterial colonization. Transgenic mice carrying candidate genetic variants, or with the deletion of candidate genes mimicking the deleterious loss-of-function variant effect, provide experimental evidence validating the biologic relevance of the novel markers associated with the microbial phenotype identified through a statistical approach. Further refinement in bioinformatics, data management approaches, or statistical tools, are required to gain insight into host-microbe interactions by harmonizing the multidimensional "big" data at the genomic, transcriptional, and proteomic levels.

Keywords: genome-wide association study (GWAS); inflammation; microbiome; periodontitis; transcriptome.

© 2019 The Authors. Periodontology 2000 Published by John Wiley & Sons Ltd.

Figures

Figure 1

Both of the single nucleotide polymorphisms rs4074082 and rs9772881 are significantly associated with periodontal complex trait 3 (PCT3 or Aggregatibacter actinomycetemcomitans trait) (P < 5 × 10−8). Manhattan plot for PCT3 (A) and locuzoom view of rs4074082 (B) are presented

Figure 2

Plakophilin 2 (PKP2) loss‐of‐function inhibits cell proliferation and cell‐to‐cell contact. PKP2 knockdown in primary gingival epithelial cells significantly hindered cell proliferation, as assayed by the MTS assay (A) and impaired cell spreading with increased gaps among cells 1‐h post‐seeding (B)

Figure 3

TRAF3 interacting protein‐2 (Traf3ip2)−/− mice harbored more Porphyromonas gingivalis A7436 and had less neutrophil infiltration than age‐matched wild‐type (WT) control animals. Mice were orally inoculated with P. gingivalis A7436 for 14 d. Plaque samples were collected 2 d after the last inoculation and P. gingivalis was quantified by real‐time quantitative PCR against a standard. (A) Significantly more P. gingivalis was present in oral plaque from Traf3ip2−/− mice than in oral plaque from wild‐type controls (*P = .008 Mann‐Whitney test). (B) Fewer neutrophils (leukocyte antigen‐6‐gene‐positive cells stained by immunohistochemistry, as indicated by arrows) were present in the gingival tissue of Traf3ip2−/− mice (upper panel) than in the WT controls (lower panel); E, enamel

Figure 4

Global profiling or “‐omics” data sets obtained from the host and plaque biofilm are integrated through refined bioinformatics, computational biology, and statistics tools to evaluate the host's determinates on bacterial colonization in plaque biofilm and host responses to a dysbiotic microflora in the subgingival environment. GWA, genome‐wide association analysis; rRNA, ribosomal RNA