Oral Microbiome and Gingival Gene Expression of Inflammatory Biomolecules With Aging and Periodontitis

An overview of the microbiota of the oral cavity of humans and non-human primates with periodontal disease: Current issues and perspectives

OBJECTIVE

To provide a comprehensive summary of the available evidence on the oral microbiota of humans and non-human primates about the etiology of periodontal disease.

DESIGN

An integrative literature review was conducted on 398 clinical and observational articles published between 2010 and 2024 using searches in the MEDLINE/PubMed, Virtual Health Library, and SciELO databases. After the screening, eligibility, data extraction, and methodological quality assessment, 21 studies were selected.

RESULTS

The results, which reveal striking similarities between the pathogens involved in periodontal disease in humans and NHPs, confirm the potential of NHPs as research models and inspire further research in this area.

CONCLUSION

According to these studies, Actinomyces spp., Aggregatibacter actinomycetemcomitans, Campylobacter rectus, Capnocytophaga spp., Eubacterium spp., Filifactor alocis, Fusobacterium spp., Leptotrichia spp., Neisseria mucosa, Parvimonas micra, Porphyromonas spp., Prevotella spp., Selenomonas spp., Streptococcus spp., Treponema spp., Tannerella spp., Veillonella parvula, were the genus and/or species of bacteria found in humans. On the other hand, Aggregatibacter acinomycetemcomitans, Campylobacter rectus, Desulfobulbus spp., Dialister invisus, Eikenella corrodens, Filifactor alocis, Fusobacterium spp., Parvimonas micra, Porphyromonas spp., Prevotella spp., Staphylococcus spp., Streptococcus spp., Treponema spp., Tannerella spp., Veillonella spp., were the most reported in NHPs. No study in non-human primates reported the presence of protozoa, unlike studies in humans that reported the presence of Entamoeba gingivalis and Trichomonas tenax. However, its role in periodontal disease still needs to be elucidated, despite the strong association mainly with severe periodontal disease where protozoa are observed in injured tissues.

Use of Nonhuman Primates in Periodontal Disease Research: Contribution of the Caribbean Primate Research Center and Cayo Santiago Rhesus Colony

This review article provides a historical summary regarding the use, value, and validity of the nonhuman primate model of periodontal disease. The information provided cites results regarding the features of naturally occurring periodontitis in various nonhuman primate species, as well as the implementation of a model of experimental periodontitis. Clinical similarities to human disease are discussed, as well as the use of these models to document physiological and pathophysiological tissue changes in the periodontium related to the initiation and progression of the disease. Additionally, the use of these analytics in examination of the tissue characteristics of the disease, and the utility of nonhuman primates in testing and describing various therapeutic modalities are described. As periodontitis represents a disease of an oral microbiome dysbiosis, features of the altered microbiome in the disease in nonhuman primates are related to similar findings in the human condition. The review then provides a summary of the features of local and systemic host responses to a periodontal infection in an array of nonhuman primate species. This includes attributes of innate immunity, acute and chronic inflammation, and adaptive immune responses. Finally, extensive information is presented regarding the role of Macaca mulatta derived from the Cayo Santiago community in evaluating critical biologic details of disease initiation, progression, and resolution. This unique resource afforded the capacity to relate risk and expression of disease and traits of the responses to age, sex, and matriline derivation (e.g., heritability) of the animals. The Cayo Santiago colony continues to provide a critical preclinical model for assessment of molecular aspects of the disease process that can lead to both new targets for therapeutics and consideration of vaccine approaches to preventing and/or treating this global disease.

Cellular senescence: A new perspective on the suppression of periodontitis (Review)

Cellular senescence, characterized by cell cycle arrest, can result in tissue dysfunction when senescent cells persist and accumulate. Periodontitis, a chronic inflammatory condition caused by the interaction between bacteria and the immune system of the host, primarily manifests as damage to periodontal tissues. Aging and inflammation are interlinked processes that exacerbate each other. The progression of localized chronic periodontal inflammation is often accelerated in conjunction with tissue and organ aging. The presence of senescent cells and release of inflammatory cytokines, immune modulators, growth factors and proteases that are associated with the senescence‑associated secretory phenotype contribute to the deterioration of periodontal tissues. The present review aimed to elucidate the mechanisms of cellular senescence and its potential impact on periodontitis, offering novel insights for modulating the inflammatory microenvironment of periodontal tissues.

The Gut and Skin Microbiome and Its Association with Aging Clocks

Aging clocks are predictive models of biological age derived from age-related changes, such as epigenetic changes, blood biomarkers, and, more recently, the microbiome. Gut and skin microbiota regulate more than barrier and immune function. Recent studies have shown that human microbiomes may predict aging. In this narrative review, we aim to discuss how the gut and skin microbiomes influence aging clocks as well as clarify the distinction between chronological and biological age. A literature search was performed on PubMed/MEDLINE databases with the following keywords: "skin microbiome" OR "gut microbiome" AND "aging clock" OR "epigenetic". Gut and skin microbiomes may be utilized to create aging clocks based on taxonomy, biodiversity, and functionality. The top contributing microbiota or metabolic pathways in these aging clocks may influence aging clock predictions and biological age. Furthermore, gut and skin microbiota may directly and indirectly influence aging clocks through the regulation of clock genes and the production of metabolites that serve as substrates or enzymatic regulators. Microbiome-based aging clock models may have therapeutic potential. However, more research is needed to advance our understanding of the role of microbiota in aging clocks.

Impact of Fixed Partial Dentures on Oral Microbial Flora and Gingival Health: An In Vitro Assessment of Salivary Microbial Profiles

Introduction The oral cavity hosts diverse microorganisms affected by factors like pH, temperature, and oxygen levels, influencing disease potential. Dentists manage oral diseases and improve aesthetics using durable restorations. Understanding periodontal response to crowns and fixed partial dentures (FPDs) is essential for effective treatment. This study aims to assess the impact of FPDs on periodontal health by comparing microbial colonies in individuals with and without FPDs. The hypothesis is that there will be no difference in microbial flora and gingival health between the two groups. Materials and methods This in vitro study utilized 40 salivary samples divided into two groups: 20 from patients with FPDs/crowns (Group 1) and 20 from patients without (Group 2). Unstimulated saliva was collected, diluted, and cultured on nutrient agar and Sabouraud Dextrose Agar to quantify anaerobic bacteria and Candida colonies. Colony counts were scored from 0 to IV based on colony-forming unit (CFU), and microscopic examination identified the types of microbes present. Data were analyzed using an unpaired t-test with IBM SPSS Statistics for Windows, Version 26 (Released 2019; IBM Corp., Armonk, New York, United States), with significance set at p < 0.05. Results The independent t-test analysis showed significantly higher mean CFUs of anaerobic microbes in Group 1 (experimental) compared to Group 2 (control) (p = 0.000). However, mean CFUs of Candida did not significantly differ between groups (p = 0.194). Microscopic examination identified Enterococcus faecalis, Pseudomonas aeruginosa, Candida albicans, Staphylococcus aureus, and Streptococcus mutans in the experimental group, whereas the control group contained only Staphylococcus aureus and Streptococcus mutans. Conclusion Individuals with FPDs exhibit higher concentrations of anaerobic microbes and specific bacteria, suggesting an increased risk of gingival inflammation and emphasizing the importance of maintaining good oral hygiene.

Fusobacterium nucleatum triggers senescence phenotype in gingival epithelial cells

The prevalence of periodontitis increases with physiological aging. However, whether bacteria associated with periodontal diseases foster aging and the mechanisms by which they may do so are unknown. Herein, we hypothesize that Fusobacterium nucleatum, a microorganism associated with periodontitis and several other age-related disorders, triggers senescence, a chief hallmark of aging responsible to reduce tissue repair capacity. Our study analyzed the senescence response of gingival epithelial cells and their reparative capacity upon long-term exposure to F. nucleatum. Specifically, we assessed (a) cell cycle arrest by analyzing the cyclin-dependent kinase inhibitors p16INK4a and p14ARF and their downstream cascade (pRb, p53, and p21) at both gene and protein levels, (b) lysosomal mediated dysfunction by using assays targeting the expression and activity of the senescence-associated β-galactosidase (SA-β-Gal) enzyme, and (c) nuclear envelope breakdown by assessing the expression of Lamin-B1. The consequences of the senescence phenotype mediated by F. nucleatum were further assessed using wound healing assays. Our results revealed that prolonged exposure to F. nucleatum promotes an aging-like phenotype as evidenced by the increased expression of pro-senescence markers (p16INK4a , p21, and pRb) and SA-β-Gal activity and reduced expression of the counter-balancing cascade (p14ARF and p53) and Lamin-B1. Furthermore, we also noted impaired wound healing capacity of gingival epithelial cells upon prolong bacterial exposure, which was consistent with the senescence-induced phenotype. Together, our findings provide a proof-of-concept evidence that F. nucleatum triggers a pro-senescence response in gingival epithelial cells. This might affect periodontal tissue homeostasis by reducing its repair capacity and, consequently, increasing susceptibility to periodontitis during aging.

Sex-Related Effect of Aging in Gingival Gamma-Delta T Cells

Aging affects the number and function of gamma-delta (γδ) T cells in a tissue-specific manner, modifying the risk for inflammatory disease. These aging-related γδT-cell variations in gingival tissues that could increase the risk for inflammation and periodontal disease remain unknown. Here we sought to identify quantitative and qualitative variations in gingival γδT cells associated with aging that could have an impact in oral immunoinflammatory responses. For this, gingival tissues from young (4 mo) and aged (24 mo) male and female mice were collected and analyzed by flow cytometry. Cell suspensions were stimulated and stained with eFluor450 (cell viability), anti-CD45 (hematopoietic cells), anti-CD3 (lymphocytes), anti-TCRγδ (γδT cells), anti-IL-15rα (cell proliferation), and anti-Notch-3 (senescence marker). Detection of intracellular cytokines IL-17A and interferon γ (IFNγ) was performed. Gingival expression of specific γ- and δ-chains and cytokines was evaluated by quantitative reverse transcription polymerase chain reaction. A significantly higher number of IL-17A-producing γδT cells and IL-17A expression levels were observed in gingival tissues from aged females but not males. Similarly, the number of gingival Notch-3+ γδT cells increased with aging only in females. IL-15rα was not detected in gingival γδT cells. Chains γ1, 2, 4, 5, 6, and 7 as well as δ1, 2, 4, and 6 were detected. Detection levels of all γ chains except γ1 as well as δ1 and δ2 changed with aging in males, females, or both. Interestingly, number of IL-17A-producing conventional T cells similarly increased with aging only in females. Both sexes showed increased IFNγ+ conventional T-cell numbers with aging; however, it reached significance only in females. In conclusion, the number of gingival IL-17A-producing γδT cells and IL-17A expression increase naturally with aging specifically in females. This sexual dimorphism in gingival γδT and conventional Th17 cell numbers and phenotypes suggests distinct aging-related mechanisms of periodontitis in males and females.

Transcriptional Signatures and Network-Based Approaches Identified Master Regulators Transcription Factors Involved in Experimental Periodontitis Pathogenesis

Periodontitis is a chronic inflammatory disease characterized by the progressive and irreversible destruction of the periodontium. Its aetiopathogenesis lies in the constant challenge of the dysbiotic biofilm, which triggers a deregulated immune response responsible for the disease phenotype. Although the molecular mechanisms underlying periodontitis have been extensively studied, the regulatory mechanisms at the transcriptional level remain unclear. To generate transcriptomic data, we performed RNA shotgun sequencing of the oral mucosa of periodontitis-affected mice. Since genes are not expressed in isolation during pathological processes, we disclose here the complete repertoire of differentially expressed genes (DEG) and co-expressed modules to build Gene Regulatory Networks (GRNs) and identify the Master Transcriptional Regulators of periodontitis. The transcriptional changes revealed 366 protein-coding genes and 42 non-coding genes differentially expressed and enriched in the immune response. Furthermore, we found 13 co-expression modules with different representation degrees and gene expression levels. Our GRN comprises genes from 12 gene clusters, 166 nodes, of which 33 encode Transcription Factors, and 201 connections. Finally, using these strategies, 26 master regulators of periodontitis were identified. In conclusion, combining the transcriptomic analyses with the regulatory network construction represents a powerful and efficient strategy for identifying potential periodontitis-therapeutic targets.

Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.

Impact of the host response and osteoblast lineage cells on periodontal disease

Periodontitis involves the loss of connective tissue attachment and alveolar bone. Single cell RNA-seq experiments have provided new insight into how resident cells and infiltrating immune cells function in response to bacterial challenge in periodontal tissues. Periodontal disease is induced by a combined innate and adaptive immune response to bacterial dysbiosis that is initiated by resident cells including epithelial cells and fibroblasts, which recruit immune cells. Chemokines and cytokines stimulate recruitment of osteoclast precursors and osteoclastogenesis in response to TNF, IL-1β, IL-6, IL-17, RANKL and other factors. Inflammation also suppresses coupled bone formation to limit repair of osteolytic lesions. Bone lining cells, osteocytes and periodontal ligament cells play a key role in both processes. The periodontal ligament contains cells that exhibit similarities to tendon cells, osteoblast-lineage cells and mesenchymal stem cells. Bone lining cells consisting of mesenchymal stem cells, osteoprogenitors and osteoblasts are influenced by osteocytes and stimulate formation of osteoclast precursors through MCSF and RANKL, which directly induce osteoclastogenesis. Following bone resorption, factors are released from resorbed bone matrix and by osteoclasts and osteal macrophages that recruit osteoblast precursors to the resorbed bone surface. Osteoblast differentiation and coupled bone formation are regulated by multiple signaling pathways including Wnt, Notch, FGF, IGF-1, BMP, and Hedgehog pathways. Diabetes, cigarette smoking and aging enhance the pathologic processes to increase bone resorption and inhibit coupled bone formation to accelerate bone loss. Other bone pathologies such as rheumatoid arthritis, post-menopausal osteoporosis and bone unloading/disuse also affect osteoblast lineage cells and participate in formation of osteolytic lesions by promoting bone resorption and inhibiting coupled bone formation. Thus, periodontitis involves the activation of an inflammatory response that involves a large number of cells to stimulate bone resorption and limit osseous repair processes.

Lipidomic analysis reveals altered lipid profiles of gingival tissues with periodontitis

AIM

The role of lipids in periodontitis has not been well studied. Thus, this study aimed to explore periodontitis-associated lipid profile changes and identify differentially expressed lipid metabolites in gingival tissues.

MATERIALS AND METHODS

Gingival tissues from 38 patients with periodontitis (periodontitis group) and 38 periodontally healthy individuals (control group) were collected. A UHPLC-QTOF-MS-based non-targeted metabolomics platform was used to identify and compare the lipid profiles of the two groups. The distribution and expression of related proteins were subsequently analyzed via immunohistochemistry to further validate the identified lipids.

RESULTS

Lipid profiles significantly differed between the two groups, and 20 differentially expressed lipid species were identified. Lysophosphatidylcholines (lysoPCs), diacylglycerols (DGs), and phosphatidylethanolamines (PEs) were significantly upregulated, while triacylglycerols (TGs) were downregulated in the periodontitis group. Moreover, the staining intensity of ABHD5/CGI-58, secretory phospholipase A2 (sPLA2), and sPLA2-IIA was significantly stronger in the gingival tissues of patients with periodontitis than in those of healthy controls.

CONCLUSIONS

LysoPCs, DGs, and PEs were significantly upregulated, whereas TGs were downregulated in gingival tissues of patients with periodontitis. Correspondingly, the immunohistochemical staining of ABHD5/CGI-58, sPLA2, and sPLA2-IIA in gingival tissues was consistent with the downstream production of lipid classes (lysoPCs, TGs, and DGs).