Subgingival Microbiome Research Articles

A pilot study of red complex and three genera subgingival microbiome in periodontitis subjects with and without diabetes, evaluated by MinION platform

Background: Subgingival niche is one biofilm habitat containing rich microbiota, which plays an active role in maintaining the health of periodontal tissue and determining host response. As such, a study of changing subgingival biofilms is important for understanding the effect of a systemic condition. In this study, we compared the occurrence of six bacteria cohabiting in the subgingival area of periodontitis subjects, with (DP, n = 8) and without (NDP, n = 4) diabetes. Methods: The six genus and species of targeted bacteria were confirmed by 16S rRNA amplicon sequencing on MinION nanopore platform. Descriptive statistic was used to describe the obtained data. Results: We found that the six genus and species of targeted bacteria were detected but in different quantities in either group's periodontal pocket. Our data showed that Tannerella forsythia was the most abundant species in subgingival biofilms of the DP group of the red complex bacteria. In contrast, Aggregatibacter sp., which belongs to the phylum of proteobacteria, was present at a relatively lower level. In contrast, Fusobacterium sp., which belongs to orange complex bacteria, showed relative similarities in subgingival biofilms of both groups tested, while Veillonella sp., were abundant in the DP groups. Conclusions: Our data show that the diversity of classic periodontopathogens increased in the subgingival niche of periodontitis subjects with diabetes. It is the first study in Indonesia to apply MinION-based, full-length 16S rRNA amplicon sequencing in periodontitis patients with and without diabetes.

Oral Microbiome in Relation to Periodontitis Severity and Systemic Inflammation.

Systemic inflammation induced by periodontitis is suggested to be the link between periodontitis and cardiovascular disease. The aim of this work was to explore the oral microbiome in periodontitis in relation to disease severity and systemic inflammation. The saliva and subgingival microbiome from periodontal pocket samples of patients with severe (n = 12) and mild periodontitis (n = 13) were analyzed using metagenomic shotgun sequencing. The taxa and pathways abundances were quantified. The diversity was assessed and the abundances to phenotype associations were performed using ANCOM and linear regression. A panel of inflammatory markers was measured in blood and was associated with taxa abundance. The microbial diversity and species richness did not differ between severe and mild periodontitis in either saliva or periodontal pockets. However, there were significant differences in the microbial composition between severe and mild periodontitis in the subgingival microbiome (i.e., pocket samples) and, in a lower grade, in saliva, and this is positively associated with systemic inflammatory markers. The “red complex” and “cluster B” abundances in periodontal pockets were strongly associated with inflammatory markers interleukin-6 and the white blood cell count. Our data suggest that systemic inflammation in severe periodontitis may be driven by the oral microbiome and may support the indirect (inflammatory) mechanism for the association between periodontitis and cardiovascular disease.

Short-term improvement of clinical parameters and microbial diversity in periodontitis patients following Indocyanine green-based antimicrobial photodynamic therapy: A randomized single-blind split-mouth cohort

BackgroundIndocyanine green-mediated photodynamic therapy is effective against chronic periodontitis. Here, we evaluated the efficiency of indocyanine green-based adjunctive antimicrobial photodynamic therapy in non-surgical treatment of chronic periodontitis patients. MethodsFifty-six periodontally involved teeth of 20 patients were treated with “scaling and root planing” (control group) or “scaling and root planing with indocyanine green-based (perio-green, 0.1 mg/ml) antimicrobial photodynamic therapy” (test group) using a split-mouth design. We performed clinical assessment of probing depth, gingival recession, clinical attachment loss, and other indices, while plaque samples were collected for microbiome analysis. ResultsAt baseline, periodontal depth and clinical attachment loss were significantly higher in the test group (p < 0.05), and at 1-month post-treatment, we observed a significant favorable reduction of both periodontal depth and clinical attachment loss in test and control sites, with lower means maintained at 3 months (p = 0.01 and p = 0.000, respectively). Additionally, analysis of variance showed significant improvements in periodontal depth and clinical attachment loss in the indocyanine green–antimicrobial photodynamic therapy group (p = 0.001), although not for clinical attachment loss in controls (p = 0.102). Moreover, a significant reduction was observed in test sites for bleeding on probing and residual pocket post-therapy (p = 0.04 and p = 0.0001 respectively). Furthermore, microbiome analysis identified Porphyromonons gingivalis, Treponema, and Tannerella in all samples with favorable changes in test sites (p = 0.07). ConclusionWe observed a significant reduction in periodontal clinical parameters (periodontal depth and clinical attachment loss) in chronic periodontitis patients treated with antimicrobial photodynamic therapy as an adjunctive procedure to conventional scaling and root planing. This improvement was associated with periodontal pathogen reduction and increase in the healthy subgingival microbiome.

The Chairside Periodontal Diagnostic Toolkit: Past, Present, and Future.

Periodontal diseases comprise a group of globally prevalent, chronic oral inflammatory conditions caused by microbial dysbiosis and the host immune response. These diseases specifically affect the tooth-supporting tissues (i.e., the periodontium) but are also known to contribute to systemic inflammation. If left untreated, periodontal diseases can ultimately progress to tooth loss, lead to compromised oral function, and negatively impact the overall quality of life. Therefore, it is important for the clinician to accurately diagnose these diseases both early and accurately chairside. Currently, the staging and grading of periodontal diseases are based on recording medical and dental histories, thorough oral examination, and multiple clinical and radiographic analyses of the periodontium. There have been numerous attempts to improve, automate, and digitize the collection of this information with varied success. Recent studies focused on the subgingival microbiome and the host immune response suggest there is an untapped potential for non-invasive oral sampling to assist clinicians in the chairside diagnosis and, potentially, prognosis. Here, we review the available toolkit available for diagnosing periodontal diseases, discuss commercially available options, and highlight the need for collaborative research initiatives and state-of-the-art technology development across disciplines to overcome the challenges of rapid periodontal disease diagnosis.

Taxonomic and Gene Category Analyses of Subgingival Plaques from a Group of Japanese Individuals with and without Periodontitis.

Periodontitis is an inflammation of tooth-supporting tissues, which is caused by bacteria in the subgingival plaque (biofilm) and the host immune response. Traditionally, subgingival pathogens have been investigated using methods such as culturing, DNA probes, or PCR. The development of next-generation sequencing made it possible to investigate the whole microbiome in the subgingival plaque. Previous studies have implicated dysbiosis of the subgingival microbiome in the etiology of periodontitis. However, details are still lacking. In this study, we conducted a metagenomic analysis of subgingival plaque samples from a group of Japanese individuals with and without periodontitis. In the taxonomic composition analysis, genus Bacteroides and Mycobacterium demonstrated significantly different compositions between healthy sites and sites with periodontal pockets. The results from the relative abundance of functional gene categories, carbohydrate metabolism, glycan biosynthesis and metabolism, amino acid metabolism, replication and repair showed significant differences between healthy sites and sites with periodontal pockets. These results provide important insights into the shift in the taxonomic and functional gene category abundance caused by dysbiosis, which occurs during the progression of periodontal disease.

Subgingival microbiome of deep and shallow periodontal sites\xa0in patients with rheumatoid arthritis: a pilot study

BackgroundSubgingival microbiome in disease-associated subgingival sites is known to be dysbiotic and significantly altered. In patients with rheumatoid arthritis (RA), the extent of dysbiosis in disease- and health-associated subgingival sites is not clear.Methods8 RA and 10 non-RA subjects were recruited for this pilot study. All subjects received full oral examination and underwent collection of subgingival plaque samples from both shallow (periodontal health-associated, probing depth ≤ 3mm) and deep subgingival sites (periodontal disease-associated, probing depth ≥ 4 mm). RA subjects also had rheumatological evaluation. Plaque community profiles were analyzed using 16 S rRNA sequencing.ResultsThe phylogenetic diversity of microbial communities in both RA and non-RA controls was significantly higher in deep subgingival sites compared to shallow sites (p = 0.022), and the overall subgingival microbiome clustered primarily according to probing depth (i.e. shallow versus deep sites), and not separated by RA status. While a large number of differentially abundant taxa and gene functions was observed between deep and shallow sites as expected in non-RA controls, we found very few differentially abundant taxa and gene functions between deep and shallow sites in RA subjects. In addition, compared to non-RA controls, the UniFrac distances between deep and shallow sites in RA subjects were smaller, suggesting increased similarity between deep and shallow subgingival microbiome in RA. Streptococcus parasanguinis and Actinomyces meyeri were overabundant in RA subjects, while Gemella morbillorum, Kingella denitrificans, Prevotella melaninogenica and Leptotrichia spp. were more abundant in non-RA subjects.ConclusionsThe aggregate subgingival microbiome was not significantly different between individuals with and without rheumatoid arthritis. Although the differences in the overall subgingival microbiome was driven primarily by probing depth, in contrast to the substantial microbiome differences typically seen between deep and shallow sites in non-RA patients, the microbiome of deep and shallow sites in RA patients were more similar to each other. These results suggest that factors associated with RA may modulate the ecology of subgingival microbiome and its relationship to periodontal disease, the basis of which remains unknown but warrants further investigation.

Anna Karenina and the subgingival microbiome associated with periodontitis

BackgroundAlthough localized aggressive periodontitis (LAP), generalized aggressive periodontitis (GAP), and chronic periodontitis (CP) are microbially driven diseases, our inability to separate disease-specific associations from those common to all three forms of periodontitis has hampered biomarker discovery. Therefore, we aimed to map the genomic content of, and the biological pathways encoded by, the microbiomes associated with these clinical phenotypes. We also estimated the extent to which these biomes are governed by the Anna Karenina principle (AKP), which states that eubiotic communities are similar between individuals while disease-associated communities are highly individualized.MethodsWe collected subgingival plaque from 25 periodontally healthy individuals and diseased sites of 59 subjects with stage 3 periodontitis and used shotgun metagenomics to characterize the aggregate of bacterial genes.ResultsBeta-dispersion metrics demonstrated that AKP was most evident in CP, followed by GAP and LAP. We discovered broad dysbiotic signatures spanning the three phenotypes, with over-representation of pathways that facilitate life in an oxygen-poor, protein- and heme-rich, pro-oxidant environment and enhance capacity for attachment and biofilm formation. Phenotype-specific indicators were more readily evident in LAP microbiome than GAP or CP. Genes that enable acetate-scavenging lifestyle, utilization of alternative nutritional sources, oxidative and nitrosative stress responses, and siderophore production were unique to LAP. An attenuation of virulence-related functionalities and stress response from LAP to GAP to CP was apparent. We also discovered that clinical phenotypes of disease resolved variance in the microbiome with greater clarity than the newly established grading system. Importantly, we observed that one third of the metagenome of LAP is unique to this phenotype while GAP shares significant functional and taxonomic features with both LAP and CP, suggesting either attenuation of an aggressive disease or an early-onset chronic disease.ConclusionWithin the limitations of a small sample size and a cross-sectional study design, the distinctive features of the microbiomes associated with LAP and CP strongly persuade us that these are discrete disease entities, while calling into question whether GAP is a separate disease, or an artifact induced by cross-sectional study designs. Further studies on phenotype-specific microbial genes are warranted to explicate their role in disease etiology.542UkY-RA6fKgB5kXgVxbtVideo

Drift of the Subgingival Periodontal Microbiome during Chronic Periodontitis in Type 2 Diabetes Mellitus Patients.

Since periodontitis and type 2 diabetes mellitus are complex diseases, a thorough understanding of their pathogenesis requires knowing the relationship of these pathologies with other disorders and environmental factors. In this study, the representability of the subgingival periodontal microbiome of 46 subjects was studied by 16S rRNA gene sequencing and shotgun sequencing of pooled samples. We examined 15 patients with chronic periodontitis (CP), 15 patients with chronic periodontitis associated with type 2 diabetes mellitus (CPT2DM), and 16 healthy subjects (Control). The severity of generalized chronic periodontitis in both periodontitis groups of patients (CP and CPT2DM) was moderate (stage II). The male to female ratios were approximately equal in each group (22 males and 24 females); the average age of the subjects was 53.9 ± 7.3 and 54.3 ± 7.2 years, respectively. The presence of overweight patients (Body Mass Index (BMI) 30–34.9 kg/m2) and patients with class 1–2 obesity (BMI 35–45.9 kg/m2) was significantly higher in the CPT2DM group than in patients having only chronic periodontitis or in the Control group. However, there was no statistically significant difference in all clinical indices between the CP and CPT2DM groups. An analysis of the metagenomic data revealed that the alpha diversity in the CPT2DM group was increased compared to that in the CP and Control groups. The microbiome biomarkers associated with experimental groups were evaluated. In both groups of patients with periodontitis, the relative abundance of Porphyromonadaceae was increased compared to that in the Control group. The CPT2DM group was characterized by a lower relative abundance of Streptococcaceae/Pasteurellaceae and a higher abundance of Leptotrichiaceae compared to those in the CP and Control groups. Furthermore, the CP and CPT2DM groups differed in terms of the relative abundance of Veillonellaceae (which was decreased in the CPT2DM group compared to CP) and Neisseriaceae (which was increased in the CPT2DM group compared to CP). In addition, differences in bacterial content were identified by a combination of shotgun sequencing of pooled samples and genome-resolved metagenomics. The results indicate that there are subgingival microbiome-specific features in patients with chronic periodontitis associated with type 2 diabetes mellitus.

Nitrate-rich diet alters the composition of the oral microbiota in periodontal recall patients.

This follow-up study evaluated microbiome changes in periodontal recall patients after consuming a nitrate-rich diet that led to a marked decrease of gingival inflammation. Subgingival microbial samples of 37 patients suffering from gingival inflammation with reduced periodontium were taken before professional mechanical plaque removal (baseline) and subsequently after 2 weeks of regularly consuming a lettuce juice beverage (day 14) containing a daily dosage of 200mg of nitrate (test group, n=18) or being void of nitrate (placebo group, n=19). Three hundred base pairs paired-end sequencing of the V3-V4 hypervariable region of the 16S rDNA was performed. At baseline, there were no significant differences about the bacterial diversity parameters between the groups (Mann-Whitney U test). After intervention in the test group, Rothia and Neisseria, including species reducing nitrate, increased significantly (negative binomial regression model). Alpha diversity decreased significantly from 115.69 ± 24.30 to 96.42 ± 24.82 aRSVs/sample (P=0.04, Wilcoxon signed-rank test), accompanied by a significant change in beta diversity (P< 0.001, PERMANOVA). In the control group, however, no genus changed significantly, and alpha-, as well as beta-diversity did not change significantly. The decrease of gingival inflammation in periodontal recall patients induced by a nitrate-rich diet is accompanied by significant compositional changes within the subgingival microbiome.

Microbial signatures of health, gingivitis, and periodontitis.

The subgingival crevice harbors diverse microbial communities. Shifts in the composition of these communities occur with the development of gingivitis and periodontitis, which are considered as successive stages of periodontal health deterioration. It is not clear, however, to what extent health- and gingivitis-associated microbiota are protective, or whether these communities facilitate the successive growth of periodontitis-associated taxa. To further our understanding of the dynamics of the microbial stimuli that trigger disruptions in periodontal homeostasis, we reviewed the available literature with the aim of defining specific microbial signatures associated with different stages of periodontal dysbiosis. Although several studies have evaluated the subgingival communities present in different periodontal conditions, we found limited evidence for the direct comparison of communities in health, gingivitis, and periodontitis. Therefore, we aimed to better define subgingival microbiome shifts by merging and reanalyzing, using unified bioinformatic processing strategies, publicly available 16S ribosomal RNA gene amplicon datasets of periodontal health, gingivitis, and periodontitis. Despite inherent methodological differences across studies, distinct community structures were found for health, gingivitis, and periodontitis, demonstrating the specific associations between gingival tissue status and the subgingival microbiome. Consistent with the concept that periodontal dysbiosis is the result of a process of microbial succession without replacement, more species were detected in disease than in health. However, gingivitis-associated communities were more diverse than those from subjects with periodontitis, suggesting that certain species ultimately become dominant as dysbiosis progresses. We identified the bacterial species associated with each periodontal condition and prevalent species that do not change in abundance from one state to another (core species), and we also outlined species co-occurrence patterns via network analysis. Most periodontitis-associated species were rarely detected in health but were frequently detected, albeit in low abundance, in gingivitis, which suggests that gingivitis and periodontitis are a continuum. Overall, we provide a framework of subgingival microbiome shifts, which can be used to generate hypotheses with respect to community assembly processes and the emergence of periodontal dysbiosis.

Gingival transcriptomics of follicular T cell footprints in progressing periodontitis.

Follicular helper T cells (Tfh) cells have been identified in the circulation and in tertiary lymphoid structures in chronic inflammation. Gingival tissues with periodontitis reflect chronic inflammation, so genomic footprints of Tfh cells should occur in these tissues and may differ related to aging effects. Macaca mulatta were used in a ligature-induced periodontitis model [adult group (aged 12-23years); young group (aged 3-7years)]. Gingival tissue and subgingival microbiome samples were obtained at matched healthy ligature-induced disease and clinical resolution sites. Microarray analysis examined Tfh genes (n=54) related to microbiome characteristics documented using 16S MiSeq. An increase in the major transcription factor of Tfh cells, BCL6, was found with disease in both adult and young animals, while master transcription markers of other T cell subsets were either decreased or showed minimal change. Multiple Tfh-related genes, including surface receptors and transcription factors, were also significantly increased during disease. Specific microbiome patterns were significantly associated with profiles indicative of an increased presence/function of Tfh cells. Importantly, unique microbial complexes showed distinctive patterns of interaction with Tfh genes differing in health and disease and with the age of the animals. An increase in Tfh cell responsiveness occurred in the progression of periodontitis, affected by age and related to specific microbial complexes in the oral microbiome. The capacity of gingival Tfh cells to contribute to localized B cell activation and active antibody responses, including affinity maturation, may be critical for controlling periodontal lesions and contributing to limiting and/or resolving the lesions.

A pilot study of red complex and three genera subgingival microbiome in periodontitis subjects with and without diabetes, evaluated by MinION platform

Background: Subgingival niche is one biofilm habitat containing rich microbiota, which plays an active role in maintaining the health of periodontal tissue and determining host response. As such, a study of changing subgingival biofilms is important for understanding the effect of a systemic condition. In this study, we compared the occurrence of six bacteria cohabiting in the subgingival area of periodontitis subjects, with (DP, n = 8) and without (NDP, n = 4) diabetes. Methods: The six genus and species of targeted bacteria were confirmed by 16S rRNA amplicon sequencing on MinION nanopore platform. Descriptive statistic was used to describe the obtained data. Results: We found that the six genus and species of targeted bacteria were detected but in different quantities in either group's periodontal pocket. Our data showed that Tannerella forsythia was the most abundant species in subgingival biofilms of the DP group of the red complex bacteria. In contrast, Aggregatibacter sp., which belongs to the phylum of proteobacteria, was present at a relatively lower level. In contrast, Fusobacterium sp., which belongs to orange complex bacteria, showed relative similarities in subgingival biofilms of both groups tested, while Veillonella sp., were abundant in the DP groups. Conclusions: Our data show that the diversity of classic periodontopathogens increased in the subgingival niche of periodontitis subjects with diabetes. It is the first study in Indonesia to apply MinION-based, full-length 16S rRNA amplicon sequencing in periodontitis patients with and without diabetes.

Efficacy of (\u2212)-epigallocatechin gallate delivered by a new-type scaler tip during scaling and root planing on chronic periodontitis: a split-mouth, randomized clinical trial

Background(−)-Epigallocatechin Gallate (EGCG) as green tea catechins possessed antibacterial and anti-inflammatory effects on periodontal disease. This study was designed to evaluate the clinical and microbiological efficacy of scaling and root planing (SRP) using EGCG aqueous solution as coolants through a new-type ultrasonic scaler tip on chronic periodontitis.MethodsThis split-mouth, randomized clinical trial included 20 patients (2 drop-outs) with chronic periodontitis and the maxillary contra-lateral sides were allocated into test and control groups randomly. Through the new-type scaler tip, 762 sites with probing depth (PD) ≥ 4 mm were treated by SRP using EGCG solution or distilled water as coolants respectively. Clinical parameters and red complex pathogens in subgingival microbiome were evaluated at baseline, 3 and 6 months after treatments.ResultsDuring 6 months, the SRP plus EGCG medication contributed to additional PD reduction as 0.33 mm and gain of clinical attachment level as 0.3 mm compared with SRP alone, and approximate 8% more sites obtained PD reduction ≥ 2 mm (p < 0.05). Meanwhile, the mean relative abundance of Tannerella forsythia was significantly lower in the combined treatment group (p < 0.05).ConclusionThe purified EGCG showed the potential to improve the outcome of periodontal non-surgical treatment and the new-type scaler tip provided an alternative vehicle for subgingival medication.Trial registration The trial was registered in Chinese Clinical Trial Registry on 15 February 2020 (No.: ChiCTR2000029831, retrospectively registered). http://www.chictr.org.cn/showprojen.aspx?proj=49441.

A pilot study of red complex and three genera subgingival microbiome in periodontitis subjects with and without diabetes, evaluated by MinION platform

Background: Subgingival niche is one biofilm habitat containing rich microbiota, which plays an active role in maintaining the health of periodontal tissue and determining host response. As such, a study of changing subgingival biofilms is important for understanding the effect of a systemic condition. In this study, we compared the occurrence of six bacteria cohabiting in the subgingival area of periodontitis subjects, with (DP, n = 8) and without (NDP, n = 4) diabetes. Methods: The six genus and species of targeted bacteria were confirmed by 16S rRNA amplicon sequencing on MinION nanopore platform. Descriptive statistic was used to describe the obtained data. Results: We found that the six genus and species of targeted bacteria were detected but in different quantities in either group's periodontal pocket. Our data showed that Tannerella forsythia was the most abundant species in subgingival biofilms of the DP group of the red complex bacteria. In contrast, Aggregatibacter sp., which belongs to the phylum of proteobacteria, was present at a relatively lower level. In contrast, Fusobacterium sp., which belongs to orange complex bacteria, showed relative similarities in subgingival biofilms of both groups tested, while Veillonella sp., were abundant in the DP groups. Conclusions: Our data show that the diversity of classic periodontopathogens increased in the subgingival niche of periodontitis subjects with diabetes. It is the first study in Indonesia to apply MinION-based, full-length 16S rRNA amplicon sequencing in periodontitis patients with and without diabetes.

The impact of smoking different tobacco types on the subgingival microbiome and periodontal health: a pilot study

Smoking is a risk factor for periodontal disease, and a cause of oral microbiome dysbiosis. While this has been evaluated for traditional cigarette smoking, there is limited research on the effect of other tobacco types on the oral microbiome. This study investigates subgingival microbiome composition in smokers of different tobacco types and their effect on periodontal health. Subgingival plaques were collected from 40 individuals, including smokers of either cigarettes, medwakh, or shisha, and non-smokers seeking dental treatment at the University Dental Hospital in Sharjah, United Arab Emirates. The entire (~ 1500 bp) 16S rRNA bacterial gene was fully amplified and sequenced using Oxford Nanopore technology. Subjects were compared for the relative abundance and diversity of subgingival microbiota, considering smoking and periodontal condition. The relative abundances of several pathogens were significantly higher among smokers, such as Prevotella denticola and Treponema sp. OMZ 838 in medwakh smokers, Streptococcus mutans and Veillonella dispar in cigarette smokers, Streptococcus sanguinis and Tannerella forsythia in shisha smokers. Subgingival microbiome of smokers was altered even in subjects with no or mild periodontitis, probably making them more prone to severe periodontal diseases. Microbiome profiling can be a useful tool for periodontal risk assessment. Further studies are recommended to investigate the impact of tobacco cessation on periodontal disease progression and oral microbiome.

Dysbiosis in the oral microbiomes of anti-CCP positive individuals at risk of developing rheumatoid arthritis

ObjectivesAn increased prevalence of periodontitis and perturbation of the oral microbiome has been identified in patients with rheumatoid arthritis (RA). The periodontal pathogen Porphyromonas gingivalis may cause local citrullination of...

Alterations and Correlations in Microbial Community and Metabolome Characteristics in Generalized Aggressive Periodontitis.

This study aimed to characterize the microbial community and metabolic profiles in generalized aggressive periodontitis (AgP) using 16S ribosomal RNA (rRNA) gene high-throughput sequencing and gas chromatography-mass spectrometry (GC-MS). A total of 146 subgingival plaque samples and 50 gingival crevicular fluid (GCF) samples were collected from 24 patients with AgP and 10 periodontally healthy subjects (PH). Striking differences were observed in subgingival microbiome and GCF metabolomics between patients with AgP and PH, but not between samples with different probing depths (PDs). Metabolomics analysis combined with enrichment analysis showed that periodontitis significantly altered the concentration of compounds associated with biosynthesis of amino acids (e.g., alanine, leucine, isoleucine, and valine), galactose metabolism (e.g., myo-inositol, galactose, glucose, and hexitol), and pyrimidine metabolism (e.g., uracil, uridine, beta alanine, and thymine). Correlation analysis showed that the genera with significant difference between AgP and PH were usually significantly correlated with more metabolites, such as Aggregatibacter, Rothia, Peptostreptococcaceae_[XI][G-5], and Bacteroidaceae_[G-1]. While glucose and oxoproline had the most significant correlations with microorganisms. Our results revealed distinct microbial communities and metabolic profiles between AgP and PH. The significant correlation between microbial taxa and metabolites suggested the possible mechanisms for periodontitis. Our results also provided effective approaches for detecting periodontal disease and managing periodontitis.

Subgingival fungi, Archaea, and viruses under the omics loupe.

The microbial communities that inhabit the gingival crevice are responsible for the pathological processes that affect the periodontium. The changes in composition and function of subgingival bacteria as disease develops have been extensively studied. Subgingival communities, however, also contain fungi, Archaea, and viruses, which could contribute to the dysbiotic processes associated with periodontal diseases. High-throughput DNA sequencing has facilitated a better understanding of the mycobiome, archaeome, and virome. However, the number of studies available on the nonbacterial components of the subgingival microbiome remains limited in comparison with publications focusing on bacteria. Difficulties in characterizing fungal, archaeal, and viral populations arise from the small portion of the total metagenome mass they occupy and lack of comprehensive reference genome databases. In addition, specialized approaches potentially introducing bias are required to enrich for viral particles, while harsh methods of cell lysis are needed to recover nuclei acids from certain fungi. While the characterization of the subgingival diversity of fungi, Archaea and viruses is incomplete, emerging evidence suggests that they could contribute in different ways to subgingival dysbiosis. Certain fungi, such as Candida albicans are suggested to facilitate colonization of bacterial pathogens. Methanogenic Archaea are associated with periodontitis severity and are thought to partner synergistically with bacterial fermenters, while viruses may affect immune responses or shape microbial communities in ways incompletely understood. This review describes the manner in which omics approaches have improved our understanding of the diversity of fungi, Archaea, and viruses within subgingival communities. Further characterization of these understudied components of the subgingival microbiome is required, together with mechanistic studies to unravel their ecological role and potential contributions to dysbiosis.

Subgingival microbiome is associated with alveolar bone loss measured 5 years later in postmenopausal women.

The aim of this study was to quantify the association between subgingival microbiota and periodontal disease progression in older women, for which limited published data exist. A total of 1016 postmenopausal women, aged 53 to 81 years, completed baseline (1997 to 2001) and 5-year (2002 to 2006) dental exams that included probing depth, clinical attachment level, gingival bleeding, and radiographic alveolar crestal height (ACH). Baseline microbiota were measured in subgingival plaque using 16S rRNA sequencing. Associations between 52 microbiota we previously found statistically significantly associated with clinical periodontal disease at baseline, were examined with disease progression. The traditional Socransky microbiota complexes also were evaluated. Side-by-side radiograph comparisons were used to define progression as ≥2 teeth with ≥1mm ACH loss or ≥1 new tooth loss to periodontitis. The association between baseline centered log(2) ratio transformed microbial relative abundances and 5-year periodontal disease progression was measured with generalized linear models. Of 36 microbiota we previously showed were elevated in moderate/severe disease at baseline, 24 had statistically significantly higher baseline mean relative abundance in progressing compared with non-progressing women (P<.05, all); which included all Socransky red bacteria (P. gingivalis, T. forsythia, T. denticola). Of 16 microbiota elevated in none/mild disease at baseline, five had statistically significantly lower baseline abundance in non-progressing compared with progressing women (P< 0.05, all), including one Socransky yellow bacteria (S. oralis). When adjusted for baseline age, socioeconomic status, and self-rated general health status, odds ratios for 5-year progression ranged from 1.18 to 1.51 (per 1-standard deviation increment in relative abundance) for microbiota statistically significantly (P< 0.05) positively associated with progression, and from 0.77 to 0.82 for those statistically significantly (P< 0.05) inversely associated with progression. These associations were similar when stratified on baseline levels of pocket depth, gingival bleeding, ACH, and smoking status. These prospective results affirm clearly that subgingival microbiota are measurably elevated several years prior to progression of alveolar bone loss, and include antecedent elevations in previously undocumented taxa additional to known Socransky pathogenic complexes.

Microbiome changes in young periodontitis patients treated with adjunctive metronidazole and amoxicillin.

To our knowledge, to date, no studies have comprehensively assessed the changes occurring in the subgingival microbiome of young patients with periodontitis treated by means of mechanical and antibiotic therapy. Thus, this study aimed to use next-generation sequencing to evaluate the subgingival microbial composition of young patients with severe periodontitis treated with scaling and root planing and systemic metronidazole and amoxicillin. Subgingival samples from healthy individuals and shallow and deep sites from periodontitis patients were individually collected at baseline and 90 days post-treatment. The samples were analyzed using 16S rRNA-gene sequencing (MiSeq-Illumina) and QIIME pipeline. Differences between groups for the microbiological data were determined using principal coordinate analysis (PCoA), linear mixed models, and the PERMANOVA test. One hundred samples were collected from 10 periodontitis patients and seven healthy individuals. PCoA analysis revealed significant partitioning between pre-and post-treatment samples. No major differences in the composition of the subgingival microbiota were observed between shallow and deep sites, at baseline or at 90-days post-treatment, and the microbiome of both site categories after treatment moved closer in similarity to that observed in periodontal health. Treatment significantly improved all clinical parameters and reduced the relative abundance of classical periodontal pathogens and of Fretibacterium fastidiosum, Eubacterium saphenum, Porphyromonas endodontalis, Treponema medium, Synergistetes, TM7, and Treponema spp, and increased that of Actinomyces, Rothia, Haemophilus, Corynebacterium, and Streptococci spp. Mechanical treatment associated with metronidazole and amoxicillin promoted a beneficial change in the microbiome of young individuals with severe periodontitis.