The personal human oral microbiome obscures the effects of treatment on periodontal disease

Therapeutic Strategies and Genetic Implications for Periodontal Disease Management: A Systematic Review

The objective of this review is to identify the microbiological alterations caused by various therapy modalities by critically analyzing the current findings. We limited our search to English-language papers published between 1 January 2004 and 7 May 2024 in PubMed, Scopus, and Web of Science that were relevant to our topic. In the search approach, the Boolean keywords "microbio*" AND "periodontitis" were used. A total of 5152 papers were obtained from the databases Web of Science (2205), PubMed (1793), and Scopus (1154). This resulted in 3266 articles after eliminating duplicates (1886), and 1411 entries were eliminated after their titles and abstracts were examined. The qualitative analysis of the 22 final articles is included in this study. Research on periodontal disease shows that periodontitis alters the oral microbiome and increases antibiotic resistance. Treatments like scaling and root planing (SRP), especially when combined with minocycline, improve clinical outcomes by reducing harmful bacteria. Comprehensive mechanical debridement with antibiotics, probiotics, EMD with bone grafts, and other adjunctive therapies enhances periodontal health. Personalized treatment strategies and advanced microbial analyses are crucial for effective periodontal management and antibiotic resistance control.

Effect of mobile app-based oral hygiene instructions on clinical parameters, oral bacterial diversity, and composition of subgingival microbiota in periodontitis patients

Introduction

Oral hygiene instruction (OHI) is essential during periodontitis treatment. Various OHI approaches have been explored, including mobile apps.

Objective

To evaluate the mobile app-based OHI's effect on periodontitis management by analyzing clinical parameters and subgingival microbiota.

Methods

Forty-four periodontitis patients were randomly assigned into two groups. The test group (n = 22) received scaling and root planing (SRP), OHI, and mobile app-based OHI, whereas the control group (n = 22) received SRP and OHI. Full mouth plaque score (FMPS), bleeding on probing (BOP) and probing pocket depth at the sampling sites (site-PPD) were assessed at baseline, one- and three-month visits. The 16S rRNA next-generation sequencing (NGS) was used to analyze subgingival plaque samples.

Results

Significant reduction in FMPS, BOP, and site-PPD at one- and three-month visits compared to baseline (p < 0.001) with no significant differences across groups (p > 0.05). In test groups, intra-group analysis showed better improvement in BOP and site-PPD (p < 0.05) than control. The diversity and composition of subgingival microbiota did not differ between groups or timepoints (p > 0.05).

Conclusions

Mobile app-based OHI showed no superior effects on improving clinical parameters and subgingival microbiota compared to conventional OHI. Further investigation into its long-term impact on periodontitis treatment is needed.

Data-driven mathematical and visualization approaches for removing rare features for Compositional Data Analysis (CoDA)

Sparse feature tables, in which many features are present in very few samples, are common in big biological data (e.g. metagenomics). Ignoring issues of zero-laden datasets can result in biased statistical estimates and decreased power in downstream analyses. Zeros are also a particular issue for compositional data analysis using log-ratios since the log of zero is undefined. Researchers typically deal with this issue by removing low frequency features, but the thresholds for removal differ markedly between studies with little or no justification. Here, we present CurvCut, an unsupervised data-driven approach with human confirmation for rare-feature removal. CurvCut implements two distinct approaches for determining natural breaks in the feature distributions: a method based on curvature analysis borrowed from thermodynamics and the Fisher-Jenks statistical method. Our results show that CurvCut rapidly identifies data-specific breaks in these distributions that can be used as cutoff points for low-frequency feature removal that maximizes feature retention. We show that CurvCut works across different biological data types and rapidly generates clear visual results that allow researchers to confirm and apply feature removal cutoffs to individual datasets.

Standardization of the protocol for oral cavity examination and collecting of the biological samples for microbiome research using the next-generation sequencing (NGS): own experience with the COVID-19 patients

To date, publications have shown that compositions of oral microbiota differ depending on their habitats (e.g. tongue, tonsils, pharynx). The absence of set standards for the choice of the areas and conditions of material collection makes the oral microbiome one of the most difficult environments for a comparative analysis with other researchers, which is a meaningful limitation during an assessment of the potential effects of microorganisms as biomarkers in the courses of various human diseases. Therefore, standardisation of basic conditions of a dental examination and collection of material for the next generation sequencing (NGS) is worth attempting. The standardisation of the dental exam and collection of the clinical materials: saliva, swab from the tongue ridge, hard palate, palatine tonsils and oropharynx, supragingival plaque and subgingival plaque. Protocol involved the patients (n = 60), assigned to 3 groups: I-COVID-19 convalescents who received antibiotics, n = 17, II-COVID-19 convalescents, n = 23 and III-healthy individuals, n = 20. The collected biological samples were used to conduct NGS (16S rRNA). The conditions of patient preparation for collecting biological materials as well as the schedule of dental examination, were proposed. Based on the research conducted, we have indicated the dental indicators that best differentiate the group of COVID-19 patients (groups I and II) from healthy people (group III). These include the DMFT, D and BOP indices. The use of alpha and beta diversity analysis provided an overall insight into the diversity of microbial communities between specific niches and patient groups. The most different diversity between the studied group of patients (group II) and healthy people (group III) was noted in relation to the supragingival plaque. The order of activities during the dental exam as well as while collecting and securing clinical materials is particularly important to avoid technical errors and material contamination which may result in erroneous conclusions from the analyses of the results of sensitive tests such as the NGS. It has been shown that the dental indices: DMFT, D number, PI and BOP are the best prognostic parameters to assess the oral health. Based on beta diversity the most sensitive niche and susceptible to changes in the composition of the microbiota is the supragingival plaque. The procedures developed by our team can be applied as ready-to-use forms in studies conducted by other researchers.

Methotrexate and Non-Surgical Periodontal Treatment Change the Oral-Gut Microbiota in Rheumatoid Arthritis: A Prospective Cohort Study

This study evaluated the changes in the composition of oral-gut microbiota in patients with rheumatoid arthritis (RA) caused by methotrexate (MTX) and non-surgical periodontal treatment (NSPT). Assessments were performed at baseline (T0), 6 months after MTX treatment (T1), and 45 days after NSPT (T2). The composition of the oral and gut microbiota was assessed by amplifying the V4 region of the 16S gene from subgingival plaques and stools. The results of the analysis of continuous variables were presented descriptively and non-parametric tests and Spearman's correlation were adopted. A total of 37 patients (27 with periodontitis) were evaluated at T0; 32 patients (24 with periodontitis) at T1; and 28 patients (17 with periodontitis) at T2. MTX tended to reduce the alpha diversity of the oral-gut microbiota, while NSPT appeared to increase the number of different species of oral microbiota. MTX and NSPT influenced beta diversity in the oral microbiota. The relative abundance of oral microbiota was directly influenced by periodontal status. MTX did not affect the periodontal condition but modified the correlations that varied from weak to moderate (p < 0.05) between clinical parameters and the microbiota. MTX and NSPT directly affected the composition and richness of the oral-gut microbiota. However, MTX did not influence periodontal parameters.

Standard operating procedures for the collection, processing, and storage of oral biospecimens at the Korea Oral Biobank Network

PURPOSE

The Korea Oral Biobank Network (KOBN) was established in 2021 as a branch of the Korea Biobank Network under the Korea Centers for Disease Control and Prevention to provide infrastructure for the collection, management, storage, and utilization of human bioresources from the oral cavity and associated clinical data for basic research and clinical studies.

METHODS

To address the need for the unification of the biobanking process, the KOBN organized the concept review for all the processes.

RESULTS

The KOBN established standard operating procedures for the collection, processing, and storage of oral samples.

CONCLUSIONS

The importance of collecting high-quality bioresources to generate accurate and reproducible research results has always been emphasized. A standardized procedure is a basic prerequisite for implementing comprehensive quality management of biological resources and accurate data production.

Association of Herpesvirus and Periodontitis: A Clinical and Laboratorial Case-Control Study

OBJECTIVES

 A significant influence of the Herpesviridae family in the progression of periodontal disease has been suggested. The aim of this study was to investigate the potential association of four Herpesviruses (HSV-1, HSV-2, cytomegalovirus [CMV], and Epstein-Barr virus [EBV]) with periodontal disease using a qualitative test for evaluating the presence or absence of viral DNA in crevicular fluid samples of both healthy periodontal patients and periodontal compromised patients.

MATERIALS AND METHODS

 A case-control study was conducted in 100 participants at a university clinic. A qualitative test was used for evaluating the presence/absence of viral DNA in crevicular fluid samples of both healthy periodontal patients and periodontal compromised patients, and considering the periodontitis staging (stage II, stage III, and stage IV) and grading (grade A, grade B, and grade C).

STATISTICAL ANALYSIS

 The distribution of the same exposure variables to the periodontitis staging and grading was compared using Chi-square, Fisher's exact, and Gamma tests depending on the variable characteristics. The significance level was set at 5%. The association of the variables: age, sex, diabetes, smoking, alcohol, and oral hygiene was also considered.

RESULTS

 The prevalence of Herpesviridae family virus DNA was 6% for the periodontal healthy group and 60% for the periodontitis group (roughly 60% on periodontitis stages II, III, and IV, p <0.001; and twofold increase in moderate and rapid progression grades compared with the slow progression grade, p <0.001). HSV1 DNA was prevalent in all periodontitis stages and grades. HSV 2, EBV, and CMV DNA had increasing prevalence rates in more severe stages (stages III and IV, p <0.001); while considering periodontitis grade, HSV2 (p = 0.001), CMV (p = 0.019) and EBV (p <0.001) DNA were prevalent only in grades B and C, with EBV DNA registering a marked prevalence in grade C.

CONCLUSION

 A significant different distribution of Herpesviridae virus DNA per each stage of disease was registered.

Comparative 16S rRNA gene sequencing study of subgingival microbiota of healthy subjects and patients with periodontitis from four different countries

AIM

To investigate the differences between the subgingival microbiota of healthy subjects (HS) and periodontitis patients (PP) from four different countries through a metagenomic approach.

MATERIALS AND METHODS

Subgingival samples were obtained from subjects from four different countries. Microbial composition was analysed through high-throughput sequencing of the V3-V4 region of the 16S rRNA gene. The country of origin, diagnosis and clinical and demographic variables of the subjects were used to analyse the microbial profiles.

RESULTS

In total, 506 subgingival samples were analysed: 196 from HS and 310 from patients with periodontitis. Differences in richness, diversity and microbial composition were observed when comparing samples pertaining to different countries of origin and different subject diagnoses. Clinical variables, such as bleeding on probing, did not significantly affect the bacterial composition of the samples. A highly conserved core of microbiota associated with periodontitis was detected, while the microbiota associated with periodontally HS was much more diverse.

CONCLUSIONS

Periodontal diagnosis of the subjects was the main variable explaining the composition of the microbiota in the subgingival niche. Nevertheless, the country of origin also had a significant impact on the microbiota and is therefore an important factor to consider when describing subgingival bacterial communities.

Longitudinal changes in subgingival biofilm composition following periodontal treatment

BACKGROUND

Current periodontal treatment involves instrumentation using hand and/or ultrasonic instruments, which are used either alone or in combination based on patient and clinician preference, with comparable clinical outcomes. This study sought to investigate early and later changes in the subgingival biofilm following periodontal treatment, to identify whether these changes were associated with treatment outcomes, and to investigate whether the biofilm responded differently to hand compared with ultrasonic instruments.

METHODS

This was a secondary-outcome analysis of a randomized-controlled trial. Thirty-eight periodontitis patients received full-mouth subgingival instrumentation using hand (n = 20) or ultrasonic instrumentation (n = 18). Subgingival plaque was sampled at baseline and 1, 7, and 90 days following treatment. Bacterial DNA was analyzed using 16S rRNA sequencing. Periodontal clinical parameters were evaluated before and after treatment.

RESULTS

Biofilm composition was comparable in both (hand and ultrasonics) treatment groups at all time points (all genera and species; p[adjusted] > 0.05). Large-scale changes were observed within groups across time points. At days 1 and 7, taxonomic diversity and dysbiosis were reduced, with an increase in health-associated genera including Streptococcus and Rothia equating to 30% to 40% of the relative abundance. When reassessed at day 90 a subset of samples reformed a microbiome more comparable with baseline, which was independent of instrumentation choice and residual disease.

CONCLUSIONS

Hand and ultrasonic instruments induced comparable impacts on the subgingival plaque microbiome. There were marked early changes in the subgingival biofilm composition, although there was limited evidence that community shifts associated with treatment outcomes.

Influence of periodontal surgery on the subgingival microbiome-A systematic review and meta-analysis

OBJECTIVE

The objective of this systematic review and meta-analysis was to evaluate the effect of periodontal surgery on the subgingival microbiome.

BACKGROUND

Periodontitis is a chronic inflammation of the tooth supporting tissues caused by the dysbiosis of the subgingival biofilm. It is managed through different non-surgical and surgical treatment modalities. Recent EFP S3 guidelines recommended performing periodontal surgery as part of Step 3 periodontitis treatment after Step 1 and Step 2 periodontal therapy, with the aim to achieve pocket closure of persisting sites. Changes in the sub-gingival microbiome may explain the treatment outcomes observed at different time points. Various microbiological detection techniques for disease-associated pathogens have been evolved over time and have been described in the literature. However, the impact of different types of periodontal surgery on the subgingival microbiome remains unclear.

METHODS

A systematic literature search was conducted in Medline, Embase, LILACS and Cochrane Library supplemented by manual search (23DEC2019, updated 21APR2022).

RESULTS

From an initial search of 3046 studies, 28 were included according to our specific inclusion criteria. Seven microbiological detection techniques were used to analyse disease-associated species in subgingival plaque samples: optical microscope, culture, polymerase chain reaction (PCR), checkerboard, enzymatic reactions, immunofluorescence and 16S gene sequencing. The included studies exhibited differences in various aspects of their methodologies such as subgingival plaque sample collection or treatment modalities. Clinical data showed a significant decrease in probing pocket depths (PPD) and clinical attachment loss (CAL) after periodontal surgery. Microbiological findings were overall heterogeneous. Meta-analysis was performed on a sub-cohort of studies all using checkerboard as a microbiological detection technique. Random effect models for Treponema denticola (T. denticola), Porphyromonas gingivalis (P. gingivalis) and Tannerella forsythia (T. forsythia) did not show a significant effect on mean counts 3 months after periodontal surgery. Notably, Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans) showed a significant increase 3 months after periodontal surgery. 16S gene sequencing was used in one included study and reported a decrease in disease-associated species with an increase in health-associated species after periodontal surgery at 3 and 6 months.

CONCLUSION

This systematic review has shown that the effect of periodontal surgery on the changes in subgingival microbiome is heterogeneous and may not always be associated with a decrease in disease-associated species. The variability could be attributed to the microbiological techniques employed for the analysis. Therefore, there is a need for well-designed and adequately powered studies to understand how periodontal surgery influences the subgingival microbiome and how the individual's microbiome affects treatment outcomes after periodontal surgery.

Subgingival host-microbiome metatranscriptomic changes following scaling and root planing in grade II/III periodontitis

AIM

To assess the effects of scaling and root planing (SRP) on the dynamics of gene expression by the host and the microbiome in subgingival plaque samples.

MATERIALS AND METHODS

Fourteen periodontitis patients were closely monitored in the absence of periodontal treatment for 12 months. During this period, comprehensive periodontal examination and subgingival biofilm sample collection were performed bi-monthly. After 12 months, clinical attachment level (CAL) data were compiled and analysed using linear mixed models (LMM) fitted to longitudinal CAL measurements for each tooth site. LMM classified the sites as stable (S), progressing (P), or fluctuating (F). After the 12-month visit, subjects received SRP, and at 15 months they received comprehensive examination and supportive periodontal therapy. Those procedures were repeated at the 18-month visit, when patients were also sampled. Each patient contributed with one S, one P, and one F site collected at the 12- and 18-month visits. Samples were analysed using Dual RNA-Sequencing to capture host and bacterial transcriptomes simultaneously.

RESULTS

Microbiome and host response behaviour were specific to the site's progression classification (i.e., S, P, or F). Microbial profiles of pre- and post-treatment samples exhibited specific microbiome changes, with progressing sites showing the most significant changes. Among them, Porphyromonas gingivalis was reduced after treatment, while Fusobacterium nucleatum showed an increase in proportion. Transcriptome analysis of the host response showed that interleukin (IL)-17, TNF signalling pathways, and neutrophil extracellular trap formation were the primary immune response activities impacted by periodontal treatment.

CONCLUSIONS

SRP resulted in a significant "rewiring" of host and microbial activities in the progressing sites, while restructuring of the microbiome was minor in stable and fluctuating sites.

Effect of Periodontal Interventions on Characteristics of the Periodontal Microbial Profile: A Systematic Review and Meta-Analysis

Our systematic review aimed to evaluate the effect of periodontal interventions on the diversity and composition of periodontal microbiota assessed by high throughput sequencing (HTS) metagenomics analysis. An electronic search was conducted from database inception to November 2021. All clinical trials that evaluated the effect of periodontal interventions on the gingival microbiota through HTS were selected. The measures of alpha diversity, richness, Shannon diversity index, and the Chao1 index, were used as the primary outcome, whereas relative abundances of bacterial genera were considered as the secondary outcome. Overall, 24 studies were eligible for the systematic review, of which 13 studies were included in the meta-analysis. Periodontal intervention for the test group decreased Shannon diversity, richness, and Chao1 index (alpha diversity), as observed from baseline to post-treatment. The most common genera that increased after periodontal therapy were Rothia, Actinomyces, Streptococcus, Veillonella, and Hemophilus, whilst Porphyromonas, Tannerella, Fusobacterium, and Treponema decreased after periodontal therapy. Periodontal interventions may decrease the bacterial diversity and richness and alter the composition of oral microbiota in the short term. Periodontal microbiota signatures could potentially be used for the assessment of periodontal disease development, progression, and success of the intervention.

Effect of electronic cigarette and tobacco smoking on the human saliva microbial community

Increasing evidence demonstrated the oral microbial community profile characteristics affected by conventional cigarettes smoking, but few studies focus on oral microbiome in response to electronic cigarettes (E-cigarettes). This study aimed to investigate the effect of E-cigarettes on the oral microbiome and to describe the difference of oral community profiles between E-cigarette smokers and tobacco smokers. 16S rRNA V4 gene sequencing was performed to investigate the oral microbial profiles of 5 E-cigarette smokers, 14 tobacco smokers, 8 quitting tobacco smokers, and 6 nonsmokers. The Chao1, ACE, and Shannon diversity indexes increased significantly in saliva samples collected from E-cigarette smokers and tobacco smokers compared to the non-smokers, and no significant difference was found in alpha diversity between E-cigarette smokers and tobacco smokers. The main phyla Proteobacteria, Firmicutes, Bacteroidetes, and Fusobacteria and major genera Neisseria, Streptococcus, Prevotellaceae, Fusobacterium, and Porphyromonas dominated in the smoking groups, while Actinobacteria, Proteobacteria, Firmicutes, Bacteroidetes, and Fusobacteria became the dominant phyla along with the genera Corynebacterium, Neisseria, Streptococcus, Actinomyces, and Porphyromonas in the nonsmokers. The differences in the phylum Actinobacteria and genus Corynebacterium contributed to various functional differences between smokers and nonsmokers. The difference on oral microbial and composition between E-cigarettes and common tobacco were associated with increased Prevotellaceae and decreased Neisseria. Additionally, smoking cessation could lead to re-establishment of the oral microbiome to that of nonsmokers. Our data demonstrate that E-cigarette smoking had different effects on the structure and composition of the oral microbial community compared to tobacco smoking. However, the short- and long-term impact of E-cigarette smoking on microbiome composition and function needs further exploration.

Impact of Oral Microbiome in Periodontal Health and Periodontitis: A Critical Review on Prevention and Treatment

The skin, oral cavity, digestive and reproductive tracts of the human body harbor symbiotic and commensal microorganisms living harmoniously with the host. The oral cavity houses one of the most heterogeneous microbial communities found in the human organism, ranking second in terms of species diversity and complexity only to the gastrointestinal microbiota and including bacteria, archaea, fungi, and viruses. The accumulation of microbial plaque in the oral cavity may lead, in susceptible individuals, to a complex host-mediated inflammatory and immune response representing the primary etiological factor of periodontal damage that occurs in periodontitis. Periodontal disease is a chronic inflammatory condition affecting about 20-50% of people worldwide and manifesting clinically through the detection of gingival inflammation, clinical attachment loss (CAL), radiographic assessed resorption of alveolar bone, periodontal pockets, gingival bleeding upon probing, teeth mobility and their potential loss in advanced stages. This review will evaluate the changes characterizing the oral microbiota in healthy periodontal tissues and those affected by periodontal disease through the evidence present in the literature. An important focus will be placed on the immediate and future impact of these changes on the modulation of the dysbiotic oral microbiome and clinical management of periodontal disease.

Microbiome profiles of non-responding and responding paired periodontitis sites within the same participants following non-surgical treatment

Aim

Periodontitis is a site-specific, chronic disease treated by non-surgical debridement of subgingival plaque. We aimed to determine the microbiome of sites that did not respond to this treatment (NR) compared with paired good responding (GR) sites before and after treatment.

Materials and methods

In a longitudinal cohort study, clinical parameters of disease and biological samples were taken prior to and 3 months after treatment. Twelve NR sites from six participants were paired with GR sites within the same participant. Subgingival plaque samples were subjected to bacterial community analysis using 16S rRNA gene sequencing.

Results

There were no significant differences in clinical parameters and microbial communities at baseline between GR and NR sites. Bacterial communities in deep pockets were dominated by a small number of species, notably Porphyromonas gingivalis and Treponema denticola. In NR sites three months after treatment there was no significant change in bacterial composition whilst there was a collapse in the abundance of pathobionts in GR sites.

Conclusion

NR sites were not identifiable prior to treatment by clinical or microbiological parameters. Treatment failed to disrupt pathogenic bacterial community in NR sites. Targeted suppression of particular species should be considered to initiate community collapse and aid disease resolution.

Nonsurgical Periodontal Treatment Options and Their Impact on Subgingival Microbiota

BACKGROUND

Different periodontal treatment methods (quadrant-wise debridement, scaling and root planing (Q-SRP), full-mouth scaling (FMS), full-mouth disinfection (FMD), and FMD with adjuvant erythritol air-polishing (FMDAP)) were applied in periodontitis patients (stage III/IV). The study objective (substudy of ClinicalTrials.gov Identifier: NCT03509233) was to compare the impact of treatments on subgingival colonization.

METHODS

Forty patients were randomized to the treatment groups. Periodontal parameters and subgingival colonization were evaluated at baseline and 3 and 6 months after treatment.

RESULTS

Positive changes in clinical parameters were recorded in every treatment group during the 3-month follow-up period, but did not always continue. In three groups, specific bacteria decreased after 3 months; however, this was associated with a renewed increase after 6 months (FMS: Porphyromonas gingivalis; FMD: Eubacterium nodatum, Prevotella dentalis; and FMDAP: uncultured Prevotella sp.).

CONCLUSIONS

The benefit of all clinical treatments measured after 3 months was associated with a decrease in pathogenic bacteria in the FMS, FMD, and FMDAP groups. However, after 6 months, we observed further improvement or some stagnation in clinical outcomes accompanied by deterioration of the microbiological profile. Investigating the subgingival microbiota might help appraise successful periodontal treatment and implement individualized therapy.

Silver Nanoparticles as Chlorhexidine and Metronidazole Drug Delivery Platforms: Their Potential Use in Treating Periodontitis

Purpose

Materials and Methods

Results

Conclusion

Long-term dynamics of the human oral microbiome during clinical disease progression

BACKGROUND

Oral microbiome dysbiosis is linked to overt inflammation of tooth-supporting tissues, leading to periodontitis, an oral condition that can cause tooth and bone loss. Microbiome dysbiosis has been described as a disruption in the symbiotic microbiota composition's stability that could adversely affect the host's health status. However, the precise microbiome dynamics that lead to dysbiosis and the progression of the disease are largely unknown. The objective of our study was to investigate the long-term dynamics of periodontitis progression and its connection to dysbiosis.

RESULTS

We studied three different teeth groups: sites that showed disease progression, sites that remained stable during the study, and sites that exhibited a cyclic deepening followed by spontaneous recovery. Time-series analysis revealed that communities followed a characteristic succession of bacteria clusters. Stable and fluctuating sites showed high asynchrony in the communities (i.e., different species responding dissimilarly through time) and a reordering of the communities where directional changes dominated (i.e., sample distance increases over time) in the stable sites but not in the fluctuating sites. Progressing sites exhibited low asynchrony and convergence (i.e., samples distance decreases over time). Moreover, new species were more likely to be recruited in stable samples if a close relative was not recruited previously. In contrast, progressing and fluctuating sites followed a neutral recruitment model, indicating that competition between closely related species is a significant component of species-species interactions in stable samples. Finally, periodontal treatment did not select similar communities but stabilized α-diversity, centered the abundance of different clusters to the mean, and increased community rearrangement.

CONCLUSIONS

Here, we show that ecological principles can define dysbiosis and explain the evolution and outcomes of specific microbial communities of the oral microbiome in periodontitis progression. All sites showed an ecological succession in community composition. Stable sites were characterized by high asynchrony, a reordering of the communities where directional changes dominated, and new species were more likely to be recruited if a close relative was not recruited previously. Progressing sites were characterized by low asynchrony, community convergence, and a neutral model of recruitment. Finally, fluctuating sites were characterized by high asynchrony, community convergence, and a neutral recruitment model.

Oral microbial diversity analysis among atrophic glossitis patients and healthy individuals

Atrophic glossitis is a common disease in oral mucosal diseases. The Current studies have found the human oral cavity contains numerous and diverse microorganisms, their composition and diversity can be changed by various oral diseases. To understand the composition and diversity of oral microbiome in atrophic glossitis is better to explore the cause and mechanism of atrophic glossitis. The salivary microbiome is comprised of indigenous oral microorganisms that are specific to each person, exhibits long-term stability. We used llumina MiSeq high-throughput sequencing based on the V3-V4 region of the bacterial 16S rRNA gene and the internal transcribed spacer (ITS) region of fungal rRNA genes from saliva in atrophic glossitis patients and healthy individuals to explore the composition and diversity of oral microbiome. In our reports, it showed a lower diversity of bacteria and fungi in atrophic glossitis patients than in healthy individuals. The data further suggests that Lactobacillus and Saccharomycetales were potential indicators for the initiation and development of atrophic glossitis. Moreover, we also discuss the relationship between the oral microbial ecology and atrophic glossitis.

Compositional Data Analysis of Periodontal Disease Microbial Communities

Periodontal disease (PD) is a chronic, progressive polymicrobial disease that induces a strong host immune response. Culture-independent methods, such as next-generation sequencing (NGS) of bacteria 16S amplicon and shotgun metagenomic libraries, have greatly expanded our understanding of PD biodiversity, identified novel PD microbial associations, and shown that PD biodiversity increases with pocket depth. NGS studies have also found PD communities to be highly host-specific in terms of both biodiversity and the response of microbial communities to periodontal treatment. As with most microbiome work, the majority of PD microbiome studies use standard data normalization procedures that do not account for the compositional nature of NGS microbiome data. Here, we apply recently developed compositional data analysis (CoDA) approaches and software tools to reanalyze multiomics (16S, metagenomics, and metabolomics) data generated from previously published periodontal disease studies. CoDA methods, such as centered log-ratio (clr) transformation, compensate for the compositional nature of these data, which can not only remove spurious correlations but also allows for the identification of novel associations between microbial features and disease conditions. We validated many of the studies’ original findings, but also identified new features associated with periodontal disease, including the genera Schwartzia and Aerococcus and the cytokine C-reactive protein (CRP). Furthermore, our network analysis revealed a lower connectivity among taxa in deeper periodontal pockets, potentially indicative of a more “random” microbiome. Our findings illustrate the utility of CoDA techniques in multiomics compositional data analysis of the oral microbiome.

Investigation of Spaceflight Induced Changes to Astronaut Microbiomes

The International Space Station (ISS) is a uniquely enclosed environment that has been continuously occupied for the last two decades. Throughout its operation, protecting the health of the astronauts on-board has been a high priority. The human microbiome plays a significant role in maintaining human health, and disruptions in the microbiome have been linked to various diseases. To evaluate the effects of spaceflight on the human microbiome, body swabs and saliva samples were collected from four ISS astronauts on consecutive expeditions. Astronaut samples were analyzed using shotgun metagenomic sequencing and microarrays to characterize the microbial biodiversity before, during, and after the astronauts’ time onboard the ISS. Samples were evaluated at an individual and population level to identify changes in microbial diversity and abundance. No significant changes in the number or relative abundance of taxa were observed between collection time points when samples from all four astronauts were analyzed together. When the astronauts’ saliva samples were analyzed individually, the saliva samples of some astronauts showed significant changes in the relative abundance of taxa during and after spaceflight. The relative abundance of Prevotella in saliva samples increased during two astronauts’ time onboard the ISS while the relative abundance of other commensal taxa such as Neisseria, Rothia, and Haemophilus decreased. The abundance of some antimicrobial resistance genes within the saliva samples also showed significant changes. Most notably, elfamycin resistance gene significantly increased in all four astronauts post-flight and a CfxA6 beta-lactam marker significantly increased during spaceflight but returned to normal levels post-flight. The combination of both shotgun metagenomic sequencing and microarrays showed the benefit of both technologies in monitoring microbes on board the ISS. There were some changes in each astronaut’s microbiome during spaceflight, but these changes were not universal for all four astronauts. Two antimicrobial resistance gene markers did show a significant change in abundance in the saliva samples of all four astronauts across their collection times. These results provide insight for future ISS microbial monitoring studies and targets for antimicrobial resistance screenings.

Streptococcus salivarius inhibits immune activation by periodontal disease pathogens

BACKGROUND

Periodontal disease represents a major health concern. The administration of beneficial microbes has been increasing in popularity over efforts to manipulate the microbes using antimicrobial agents. This study determined the ability of Streptococcus salivarius to inhibit IL-6 and IL-8 production by gingival fibroblasts when activated by periodontal pathogens and their effect on the salivary microbiome.

METHODS

Primary human gingival fibroblasts were challenged with Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans and Fusobacterium nucleatum and a combination of all three. IL-6 and IL-8 cytokine release were measured. Using this same model, S. salivarius K12, M18 and different supernatant and whole-cell lysate fractions of S. salivarius K12 were administered to pathogen-induced fibroblasts. A patient study of healthy participants was also conducted to determine the effect S. salivarius K12 had on the native microbiome using 16S next generation sequence analysis.

RESULTS

All pathogens tested induced a significant IL-6 and IL-8 response. S. salivarius K12 or M18, did not exhibit an increase in inflammatory cytokines. When either of the probiotic strains were co-administered with a pathogen, there were significant reductions in both IL-6 and IL-8 release. This effect was also observed when gingival fibroblasts were pre-treated with either S. salivarius K12 or M18 and then stimulated with the oral pathogens. Chewing gum containing S. salivarius K12 did not alter the salivary microbiome and did not increase inflammatory markers in the oral cavity.

CONCLUSION

S. salivarius K12 and M18 prevented immune activation induced by periodontal disease pathogens. S. salivarius K12 did not alter the salivary microbiome or induce immune activation when administered as a chewing gum. These results warrant further study to determine if it may be an effective treatment in a model of periodontal disease.

Metagenomic sequencing provides new insights into the subgingival bacteriome and aetiopathology of periodontitis

"Open-ended" molecular techniques such as 16S rRNA sequencing have revealed that the oral bacteriome of subgingival plaque is more diverse than originally thought. 16S rRNA analysis has demonstrated that constituents of the overall bacterial community are qualitatively similar in health and disease, differing mainly in their relative proportions with respect to each other. Species in low abundance can also act as critical species, leading to the concept of global community dysbiosis which relates to shifts in community structure, rather than shifts in membership. Correlation analysis suggests that coordinated interactions in the community are essential for incipient dysbiosis and disease pathogenesis. The subgingival bacteriome also provides biomarkers that are useful for disease detection and management. Combined with clinical and biological parameters, these may assist clinicians in developing and implementing effective treatment strategies to restore microbial homeostasis and monitor disease. Identification of higher risk groups or poor responders to treatment using unique subgingival bacteriome signatures may also lead to early intervention.

Inter-site and interpersonal diversity of salivary and tongue microbiomes, and the effect of oral care tablets

Background: Oral microbiota has been linked to both health and disease. Specifically, tongue-coating microbiota has been implicated in aspiration pneumonia and halitosis. Approaches altering one's oral microbiota have the potential to improve oral health and prevent diseases. Methods: Here, we designed a study that allows simultaneous monitoring of the salivary and tongue microbiomes during an intervention on the oral microbiota. We applied this study design to evaluate the effect of single-day use of oral care tablets on the oral microbiome of 10 healthy individuals. Tablets with or without actinidin, a protease that reduces biofilm formation in vitro, were tested. Results: Alpha diversity in the saliva was higher than that on the tongue without the intervention. The core operational taxonomic units (OTUs) common to both sites were identified. The salivary and tongue microbiomes of one individual tended to be more similar to one another than to those of other individuals. The tablets did not affect the alpha or beta diversity of the oral microbiome, nor the abundance of specific bacterial species. Conclusions: While the salivary and tongue microbiomes differ significantly in terms of bacterial composition, they show inter- rather than intra-individual diversity. A one-day usage of oral care tablets did not alter the salivary or tongue microbiomes of healthy adults. Whether the use of oral tablets for a longer period on healthy people or people with greater tongue coating accumulation shifts their oral microbiome needs to be investigated.

Inter-site and interpersonal diversity of salivary and tongue microbiomes, and the effect of oral care tablets

Background: Oral microbiota has been linked to both health and diseases. Specifically, tongue-coating microbiota has been implicated in aspiration pneumonia and halitosis. Approaches altering one's oral microbiota have the potential to improve oral health and prevent diseases. Methods: Here, we designed a study that allows simultaneous monitoring of the salivary and tongue microbiomes during an intervention on the oral microbiota. We applied this study design to evaluate the effect of single-day use of oral care tablets on the oral microbiome of 10 healthy individuals. Tablets with or without actinidin, a protease that reduces biofilm formation in vitro, were tested. Results: Alpha diversity of the tongue microbiome was significantly lower than that of the salivary microbiome, using both the number of observed amplicon sequence variants (254 ± 53 in saliva and 175 ± 37 in tongue; P = 8.9e-7, Kruskal-Wallis test) and Shannon index (6.0 ± 0.4 in saliva and 5.4 ± 0.3 in tongue; P = 2.0e-7, Kruskal-Wallis test). Fusobacterium periodonticum, Saccharibacteria sp. 352, Streptococcus oralis subsp . dentisani, Prevotella melaninogenica, Granulicatella adiacens, Campylobacter concisus, and Haemophilus parainfluenzae were the core operational taxonomic units (OTUs) common to both sites. The salivary and tongue microbiomes of one individual tended to be more similar to one another than to those of other individuals. The tablets did not affect the alpha or beta diversity of the oral microbiome, nor the abundance of specific bacterial species. Conclusions: While the salivary and tongue microbiomes differed significantly in terms of bacterial composition, they showed inter- rather than intra-individual diversity. A one-day usage of oral care tablets did not alter the salivary or tongue microbiomes of healthy adults. Whether the use of oral tablets for a longer period on healthy people or people with greater tongue coating accumulation shifts their oral microbiome needs to be investigated.

Impact of systemic factors in shaping the periodontal microbiome

Since 2010, next-generation sequencing platforms have laid the foundation to an exciting phase of discovery in oral microbiology as it relates to oral and systemic health and disease. Next-generation sequencing has allowed large-scale oral microbial surveys, based on informative marker genes, such as 16S ribosomal RNA, community gene inventories (metagenomics), and functional analyses (metatranscriptomics), to be undertaken. More specifically, the availability of next-generation sequencing has also paved the way for studying, in greater depth and breadth, the effect of systemic factors on the periodontal microbiome. It was natural to investigate systemic diseases, such as diabetes, in such studies, along with systemic conditions or states, , pregnancy, menopause, stress, rheumatoid arthritis, and systemic lupus erythematosus. In addition, in recent years, the relevance of systemic "variables" (ie, factors that are not necessarily diseases or conditions, but may modulate the periodontal microbiome) has been explored in detail. These include ethnicity and genetics. In the present manuscript, we describe and elaborate on the new and confirmatory findings unveiled by next-generation sequencing as it pertains to systemic factors that may shape the periodontal microbiome. We also explore the systemic and mechanistic basis for such modulation and highlight the importance of those relationships in the management and treatment of patients.

Did Omics change periodontal therapy?

The starting point for defining effective treatment protocols is a clear understanding of the etiology and pathogenesis of a condition. In periodontal diseases, this understanding has been hindered by a number of factors, such as the difficulty in differentiating primary pathogens from nonpathogens in complex biofilm structures. The introduction of DNA sequencing technologies, including taxonomic and functional analyses, has allowed the oral microbiome to be investigated in much greater breadth and depth. This article aims to compile the results of studies, using next-generation sequencing techniques to evaluate the periodontal microbiome, in an attempt to determine how far the knowledge provided by these studies has brought us in terms of influencing the way we treat periodontitis. The taxonomic data provided, to date, by published association and elimination studies using next-generation sequencing confirm previous knowledge on the role of classic periodontal pathogens in the pathobiology of disease and include new species/genera. Conversely, species and genera already considered as host-compatible and others less explored were associated with periodontal health as their levels were elevated in healthy individuals and increased after therapy. Functional and transcriptomic analyses also demonstrated that periodontal biofilms are taxonomically diverse, functionally congruent, and highly cooperative. Very few interventional studies to date have examined the effects of treatment on the periodontal microbiome, and such studies are heterogeneous in terms of design, sample size, sampling method, treatment provided, and duration of follow-up. Hence, it is still difficult to draw meaningful conclusions from them. Thus, although OMICS knowledge has not yet changed the way we treat patients in daily practice, the information provided by these studies opens new avenues for future research in this field. As new pathogens and beneficial species become identified, future randomized clinical trials could monitor these species/genera more comprehensively. In addition, the metatranscriptomic data, although still embryonic, suggest that the interplay between the host and the oral microbiome may be our best opportunity to implement personalized periodontal treatments. Therapeutic schemes targeting particular bacterial protein products in subjects with specific genetic profiles, for example, may be the futuristic view of enhanced periodontal therapy.

A systematic review on bacterial community changes after periodontal therapy with and without systemic antibiotics: An analysis with a wider lens

BACKGROUND

This systematic review aimed to provide a comprehensive view on microbial community shifts after periodontal therapy with and without systemic antibiotics, conducted in randomized controlled trials (RCTs).

METHODS

Search functions in PubMed, Scopus, the Web of Knowledge, and the Cochrane Oral Health Library databases were used to locate studies published up to December 2018 that reported at least two bacteria before and after periodontal therapy. Gray literature and manual searching were done. Information about reported bacteria in those studies were extracted, and a descriptive microbial community analysis was conducted to observe trends and influencing factors on microbial dynamics. Methodological aspects were examined, including the bacterial detection method, heterogeneity of procedures, and risk of bias (RoB) of the studies.

RESULTS

The 30 included studies reported 130 different bacterial genera. Four different detection methods were reported: cultivation, polymerase chain reaction, DNA-DNA-checkerboard hybridization, and 16S rDNA amplicon sequencing. No general compositional change between the antibiotic and placebo groups could be found after therapy on the community level. Fifty-five bacteria were reported in two or more studies. Of those, 24 genera decreased and 13 increased more frequently after antibiotic use. Great heterogeneity between procedures and variability in RoB were found among the studies.

CONCLUSIONS

Microbial shifts occurred regardless of the use of antibiotics. Antibiotic therapy seems to induce more changes in single bacteria. The heterogeneity in methods and reporting of the included studies preclude clinical recommendations on the use or not of adjunctive antibiotics. The present results may guide further research on the topic.

Grade C molar-incisor pattern periodontitis subgingival microbial profile before and after treatment

Aim: This study evaluated the influence of periodontal therapy on the microbiological profile of individuals with Grade C Molar-Incisor Pattern Periodontitis (C/MIP).

Methods: Fifty-three African-American participants between the ages of 5–25, diagnosed with C/MIP were included. Patients underwent full mouth mechanical debridement with systemic antibiotics (metronidazole 250 mg + amoxicillin 500 mg, tid, 7 days). Subgingival samples were collected from a diseased and a healthy site from each individual prior to treatment and at 3, 6, 12, 18 and 24 months after therapy from the same sites. Samples were subjected to a 16S rRNA gene based-microarray.

Results: Treatment was effective in reducing the main clinical parameters of disease. Aggregatibacter actinomycetemcomitans (A.a.) was the strongest species associated with diseased sites. Other species associated with diseased sites were Treponema lecithinolyticum and Tannerella forsythia. Species associated with healthy sites were Rothia dentocariosa/mucilaginosa, Eubacterium yurii, Parvimonas micra, Veillonella spp., Selenomonas spp., and Streptococcus spp. Overall, treatment was effective in strongly reducing A.a. and other key pathogens, as well as increasing health-associated species. These changes were maintained for at least 6 months.

Conclusions:Treatment reduced putative disease-associated species, particularly A.a., and shifted the microbial profile to more closely resemble a healthy-site profile. (Clinicaltrials.gov registration #NCT01330719).

Using next-generation sequencing to detect oral microbiome change following periodontal interventions: A systematic review

Objectives

This systematic review was to evaluate the change of oral microbiome based on next‐generation sequencing (NGS)‐metagenomic analysis following periodontal interventions among systematically healthy subjects.

Materials and Methods

A structured search strategy consisting of “metagenomics” and “oral diseases” was applied to PubMed, EMBASE, and Web of Science to identify effective papers. The included studies were original studies published in English, using metagenomic approach to analyze the effectiveness of periodontal intervention on oral microbiome among systematically healthy human subjects with periodontitis.

Results

A total of 12 papers were included in this review. Due to the heterogeneity of selected study, quantitative analysis was not performed. The findings as to how alpha diversity changed after interventions were not consistent across studies. Six studies illustrated clear separation of microbial composition between dental plaque samples collected before and after intervention using principal coordinates/component analysis. The most commonly detected genera before intervention were Porphyromonas, Treponema, Tannerella, and Prevotella, while Streptococcus and Actinomyces usually increased and became the dominant genera after intervention. Correlation network analysis revealed that after intervention, the topology of network was different compared to the corresponding pre‐interventional samples.

Conclusion

Existing evidence of metagenomic studies depicts a complex change in oral microbiome after periodontal intervention.

The influence of spaceflight on the astronaut salivary microbiome and the search for a microbiome biomarker for viral reactivation

BACKGROUND

Spaceflight impacts astronauts in many ways but little is known on how spaceflight affects the salivary microbiome and the consequences of these changes on astronaut health, such as viral reactivation. In order to understand this, the salivary microbiome was analyzed with 16S rRNA gene amplicon sequencing, and saliva viral titers were analyzed with quantitative polymerase chain reaction (qPCR) with primers specific for Epstein-Barr virus (EBV), herpes simplex virus (HSV), and varicella zoster virus (VZV) from 10 astronauts pre-flight, in-flight, and post-flight.

RESULTS

Streptococcus was the most abundant organism in the saliva, making up 8% of the total organisms detected, and their diversity decreased during spaceflight. Other organisms that had statistically significant changes were Proteobacteria and Fusobacteria which increased during flight and Actinobacteria which decreased during flight. At the genus level, Catonella, Megasphera, and Actinobacillus were absent in more than half of saliva samples collected pre-flight but were then detected during flight. In those subjects that already had these genera pre-flight, their relative abundances increased during flight. Correlation analyses between the microbiome and viral titers revealed a positive correlation with Gracilibacteria, Absconditabacteria, and Abiotrophia and a negative correlation between Oribacterium, Veillonella, and Haemophilus. There was also a significant positive correlation between microbiome richness and EBV viral titers.

CONCLUSIONS

This is the first study to look at how the salivary microbiome changes as a result of spaceflight and the search for bacterial biomarkers for viral reactivation. Further studies examining the role of specific organisms that were shown to be correlative and predictive in viral reactivation, a serious problem in astronauts during spaceflight, could lead to mitigation strategies to help prevent disease during both short and long duration space missions. Video abstract.

Polymicrobial periodontal disease triggers a wide radius of effect and unique virome

Periodontal disease is a microbially-mediated inflammatory disease of tooth-supporting tissues that leads to bone and tissue loss around teeth. Although bacterially-mediated mechanisms of alveolar bone destruction have been widely studied, the effects of a polymicrobial infection on the periodontal ligament and microbiome/virome have not been well explored. Therefore, the current investigation introduced a new mouse model of periodontal disease to examine the effects of a polymicrobial infection on periodontal ligament (PDL) properties, changes in bone loss, the host immune response, and the microbiome/virome using shotgun sequencing. Periodontal pathogens, namely Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia, and Fusobacterium nucleatum were used as the polymicrobial oral inoculum in BALB/cByJ mice. The polymicrobial infection triggered significant alveolar bone loss, a heightened antibody response, an elevated cytokine immune response, a significant shift in viral diversity and virome composition, and a widening of the PDL space; the latter two findings have not been previously reported in periodontal disease models. Changes in the PDL space were present at sites far away from the site of insult, indicating that the polymicrobial radius of effect extends beyond the bone loss areas and site of initial infection and wider than previously appreciated. Associations were found between bone loss, specific viral and bacterial species, immune genes, and PDL space changes. These findings may have significant implications for the pathogenesis of periodontal disease and biomechanical properties of the periodontium. This new polymicrobial mouse model of periodontal disease in a common mouse strain is useful for evaluating the features of periodontal disease.

Metagenomic Assessment of Different Interventions for Treatment of Chronic Periodontitis: A Systematic Review and Meta-Analysis

Background:

Chronic periodontitis is attributed to oral microbial imbalance and host inflammatory reaction.

Objective:

Our review addresses the question of: Are the available interventions able to regain oral microbial balance in patients having chronic periodontitis?

Data Sources:

We performed a comprehensive systematic search of MEDLine via Pubmed, Cochrane CENTRAL, Clinicalkey, Clarivate Analytics, Springer materials, Wiley, SAGE, Elsevier, Taylor & Francis group, and Wolter Kluwer, together with hand searching and searching the grey literature.

Eligibility Criteria:

We included interventional studies testing the microbiome analysis using metagenomic techniques as an outcome to any intervention for chronic periodontitis.

Study Appraisal and Synthesis Methods:

All studies were imported in Mendeley. The risk of bias was assessed using the specific tool for each study design. The results were analysed using RevMan. All the review steps were performed in duplicates.

Results:

The search yielded 2700 records. After exclusion steps, 10 records were found eligible. We included 5 RCTs, 1 non-RCT, 3 before-and-after studies, and 1 ongoing study. The studies tested non-surgical periodontal treatment with and without antibiotic coverage, probiotics, sodium hypochlorite rinse, and different toothpaste ingredients. One RCT tested the use of enamel matrix derivatives in cases with furcation involvement.

Limitations:

The eligible available studies were small in number. Also, the risk of bias and lack of a standardized protocol impaired the ability to pool all the results.

Conclusions:

The body of the available evidence is not sufficient, and future studies are recommended to better evaluate the effect of periodontal treatments on the periodontal microbiome.

The human oral cavity microbiota composition during acute tonsillitis: a cross-sectional survey

BACKGROUND

Microbial culture-based investigations of inflamed tonsil tissues have previously indicated enrichment of several microorganisms such as Streptococcus, Staphylococcus and Prevotella. These taxa were also largely reflected in DNA sequencing studies performed using tissue material. In comparison, less is known about the response of the overall oral cavity microbiota to acute tonsillitis despite their role in human health and evidence showing that their compositions are correlated with diseases such as oral cancers. In addition, the influence of subject-specific circumstances including consumption of prescription antibiotics and smoking habits on the microbiology of acute tonsillitis is unknown.

METHODS

We collected oral rinse samples from 43 individuals admitted into hospital for acute tonsillitis and 165 non-disease volunteers recruited from the public, and compared their microbial community compositions using 16S rRNA gene sequencing. We assessed the impact of tonsillitis, whether subjects were prescribed antibiotics, the presence of oral abscesses and their smoking habits on community composition, and identified specific microbial taxa associated with tonsillitis and smoking.

RESULTS

Oral rinse community composition was primarily associated with disease state (tonsillitis vs non-tonsillitis) although its effect was subtle, followed by smoking habit. Multiple Prevotella taxa were enriched in tonsillitis subjects compared to the non-tonsillitis cohort, whereas the non-tonsillitis cohort primarily showed associations with several Neisseria sequence variants. The presence of oral abscesses did not significantly influence community composition. Antibiotics were prescribed to a subset of individuals in the tonsillitis cohort but we did not observe differences in community composition associated with antibiotics consumption. In both tonsillitis and non-tonsillitis cohorts, smoking habit was associated with enrichment of several Fusobacterium variants.

CONCLUSIONS

These findings show that the oral cavity microbial community is altered during acute tonsillitis, with a consistent enrichment of Prevotella during tonsillitis raising the possibility of targeted interventions. It also supports the possible link between smoking, Fusobacteria and oral cancers.

Focal infection of periodontal origin

Periodontology has evolved from a predominantly mechanical to a sophisticated infectious disease-based discipline. Research has paved the way for a greater understanding of the periodontal microbiome, improvement in periodontal diagnostics and therapies, and the recognition of periodontitis being associated with more than 50 systemic diseases. The etiopathology of progressive periodontitis includes active herpesviruses, specific bacterial pathogens, and proinflammatory immune responses. This article points to a role of periodontal herpesviruses in the development of systemic diseases and proposes treatment of severe periodontitis not only to avoid tooth loss, but also to reduce the risk for systemic diseases. An efficient, safe, and reliable anti-infective treatment of severe periodontitis is presented, which targets both herpesviruses and bacterial pathogens and which can be carried out in minimal time with minimal cost.

Shared detection of Porphyromonas gingivalis in cohabiting family members: a systematic review and meta-analysis

Introduction: Periodontitis is an inflammatory dysbiotic disease. Among putative dysbiosis causes, transmission of Porphyromonas gingivalis between individuals of the same family remains unclear. The aim of this systematic review and meta-analysis is to assess the likelihood of shared detection of Porphyromonas gingivalis among cohabiting family members.

Methods: A literature search was conducted on different databases up to September 2018. Articles assessing the presence of P.gingivalis between members of the same family were screened. Only English literature was retrieved, whereas no limits were applied for bacterial sampling and detection methods.

Results: Overall, 26 articles published between 1993 and 2017 met the inclusion criteria. Of these, 18 articles were used for meta-analyses. Based on bacterial culture, the likelihood of an intra-familial transmission of P.gingivalis once a member of the family harbors the bacterium is estimated at 63.5% (n = 132 pairs of family members); this drops to 45% when pooling together culture and Polymerase-Chain-Reaction (n = 481 pairs), whereas it is estimated at 35.7% when genotyping is applied (n = 137 pairs).

Conclusion: Pooled results suggest that the likelihood of detecting P.gingivalis within within family members is moderately frequent. Personalized periodontal screening and prevention may consider intra-familial co-occurrence of P.gingivalis as feasible.

Species-Level Salivary Microbial Indicators of Well-Resolved Periodontitis: A Preliminary Investigation

Objective: To profile the salivary microbiomes of a Hong Kong Chinese cohort at a species-level resolution and determine species that discriminated clinically resolved periodontitis from periodontally healthy cases. Methods: Salivary microbiomes of 35 Hong Kong Chinese subjects' under routine supportive dental care were analyzed. All subjects had been treated for any dental caries or periodontal disease with all restorative treatment completed at least 1 year ago and had ≤3 residual pockets. They were categorized based on a past diagnosis of chronic periodontitis into "healthy" (H) or "periodontitis" (P) categories. Unstimulated whole saliva was collected, genomic DNA was isolated, and high throughput Illumina MiSeq sequencing of 16S rRNA (V3-V4) gene amplicons was performed. The sequences were assigned taxonomy at the species level by using a BLASTN based algorithm that used a combined reference database of HOMD RefSeqV14.51, HOMD RefSeqExtended V1.1 and GreenGeneGold. Species-level OTUs were subjected to downstream analysis in QIIME and R. For P and H group comparisons, community diversity measures were compared, differentially abundant species were determined using DESeq2, and disease indicator species were determined using multi-level pattern analysis within the R package "indicspecies." Results: P subjects were significantly older than H subjects (p = 0.003) but not significantly different in their BOP scores (p = 0.82). No significant differences were noted in alpha diversity measures after adjusting for age, gender, and BOP or in the beta diversity estimates. Four species; Treponema sp. oral taxon 237, TM7 sp. Oral Taxon A56, Prevotella sp. oral taxon 314, Prevotella sp. oral taxon 304, and Capnocytophaga leadbetteri were significantly more abundant in P than in the H group. Indicator species analysis showed 7 significant indicators species of P group. Fusobacterium sp oral taxon 370 was the sole positive indicator of P group (positive predictive value = 0.9, p = 0.04). Significant indicators of the H category were Leptotrichia buccalis, Corynebacterium matruchotii, Leptotrichia hofstadii, and Streptococcus intermedius. Conclusion: This exploratory study showed salivary microbial species could discriminate treated, well-maintained chronic periodontitis from healthy controls with similar gingival inflammation levels. The findings suggest that certain salivary microbiome features may identify periodontitis-susceptible individuals despite clinical disease resolution.

Intra-oral single-site comparisons of periodontal and peri-implant microbiota in health and disease

OBJECTIVE

Periodontitis and peri-implantitis are oral infectious-inflammatory diseases that share similarities in their pathology and etiology. Our objective was to characterize the single-site subgingival and submucosal microbiomes of implant-rehabilitated, partially dentate Chinese subjects (n = 18) presenting with both periodontitis and peri-implantitis.

MATERIALS AND METHODS

Subgingival/submucosal plaque samples were collected from four clinically distinct sites in each subject: peri-implantitis submucosa (DI), periodontal pocket (DT), clinically healthy (unaffected) peri-implant submucosa (HI), and clinically healthy (unaffected) subgingival sulcus (HT). The bacterial microbiota present was analyzed using Illumina MiSeq sequencing.

RESULTS

Twenty-six phyla and 5,726 operational taxonomic units (OTUs, 97% sequence similarity cutoff) were identified. Firmicutes, Proteobacteria, Fusobacteria, Bacteroidetes, Actinobacteria, Synergistetes, TM7, and Spirochaetes comprised 99.6% of the total reads detected. Bacterial communities within the DI, DT, HI, and HT sites shared high levels of taxonomic similarity. Thirty-one "core species" were present in >90% sites, with Streptococcus infantis/mitis/oralis (HMT-070/HMT-071/HMT-638/HMT-677) and Fusobacterium sp. HMT-203/HMT-698 being particularly prevalent and abundant. Beta-diversity analyses (PERMANOVA test, weighted UniFrac) revealed the largest variance in the microbiota was at the subject level (46%), followed by periodontal health status (4%). Differing sets of OTUs were associated with periodontitis and peri-implantitis sites, respectively. This included putative "periodontopathogens," such as Prevotella, Porphyromonas, Tannerella, Bacteroidetes [G-5], and Treponema spp. Interaction network analysis identified several putative patterns underlying dysbiosis in periodontitis/peri-implantitis sites.

CONCLUSIONS

Species (OTU) composition of the periodontal and peri-implant microbiota varied widely between subjects. The inter-subject variations in subgingival/submucosal microbiome composition outweighed differences observed between implant vs. tooth sites, or between diseased vs. healthy (unaffected) peri-implant/periodontal sites.

Vaginal lactobacilli inhibit growth and hyphae formation of Candida albicans

Lactobacillus species are the predominant vaginal microbiota found in healthy women of reproductive age and help to prevent pathogen infection by producing lactic acid, H₂O₂ and anti-microbial compounds. Identification of novel vaginal Lactobacillus isolates that exhibit efficient colonisation and secrete anti-Candida factors is a promising strategy to prevent vulvovaginal candidiasis. The azole antifungal agents used to treat vulvovaginal candidiasis elicit adverse effects such as allergic responses and exhibit drug interactions. Candida strains with resistance to antifungal treatments are often reported. In this study, we isolated Lactobacillus species from healthy Korean women and investigated their antifungal effects against C. albicans in vitro and in vivo. Lactobacillus conditioned supernatant (LCS) of L. crispatus and L. fermentum inhibited C. albicans growth in vitro. A Lactobacillus-derived compound, which was not affected by proteolytic enzyme digestion and heat inactivation, inhibited growth and hyphal induction of C. albicans after adjustment to neutral pH. Combination treatment with neutral LCSs of L. crispatus and L. fermentum effectively inhibited propagation of C. albicans in a murine in vivo model of vulvovaginal candidiasis.

No differences in microbiome changes between anti-adhesive and antibacterial ingredients in toothpastes during periodontal therapy

Aim

This subgroup analysis of a 12‐week randomized, double‐blind, and two‐center trial aimed to evaluate whether two different toothpaste formulations can differentially modulate the dental microbiome.

Material and Methods

Forty one mild to moderate periodontitis patients used as an adjunct to periodontal treatment either a toothpaste with anti‐adhesive zinc‐substituted carbonated hydroxyapatite (HA) or with antimicrobial and anti‐adhesive amine fluoride/stannous fluoride (AmF/SnF₂) during a 12‐week period. Plaque samples from buccal/lingual, interproximal, and subgingival sites were taken at baseline, 4 weeks after oral hygiene phase, and 8 weeks after periodontal therapy. Samples were analyzed with paired‐end Illumina Miseq 16S rDNA sequencing. The differences and changes on community level (alpha and beta diversity) and on the level of single agglomerated ribosomal sequence variants (aRSV) were calculated with analysis of covariance (ANCOVA) and likelihood ratio test (LRT).

Results

Interproximal and subgingival sites harbored predominately Fusobacterium and Prevotella species associated with periodontitis, whereas buccal/lingual sites harbored mainly Streptococcus and Veillonella species associated with periodontal health. Alpha and beta diversity did not change noticeably differently between both toothpaste groups (P > 0.05, ANCOVA). Furthermore, none of the aRSVs showed a noticeably different change between the tested toothpastes during periodontal therapy (P_adj .> 0.05, LRT).

Conclusion

The use of a toothpaste containing anti‐adhesive HA did not induce statistically noticeably different changes on microbial composition compared to an antimicrobial and anti‐adhesive AmF/SnF₂ formulation.

High-Throughput Sequencing Analysis of Microbial Profiles in the Dry Socket

PURPOSE

The aim of this study was to explore and describe the microbial profiles of dry socket (DS) and identify the key microbial population as a possible disease-related factor.

MATERIALS AND METHODS

Bacterial samples were collected from patients who underwent surgical mandibular third molar extraction and were divided in 3 groups: the disease (D) group composed of patients who were diagnosed with DS; the treated (T) group composed of patients from the D group who received treatment; and the control (C) group composed of patients who did not have adverse reactions after tooth extraction. Bacterial DNA was extracted and the V3 and V4 hypervariable regions of the bacterial 16S rRNA gene were amplified and subjected to sequencing. Sequence data were analyzed using alpha and beta diversity indices.

RESULTS

In total, 772,169 high-quality sequences were detected from 31 samples. Using a 97% similarity level, 531 operational taxonomic units were detected. In addition, 10 phyla, 23 classes, 38 orders, 63 families, and 116 genera were found. Composition of the microbial community in the D group differed considerably from that of the T and C groups. Furthermore, a specific microbial pattern, which included Parvimonas, Peptostreptococcus, Prevotella, Fusobacterium, Slackia, Oribacterium, and Solobacterium species, appeared abundantly in the D group compared with the T and C groups. Moreover, Parvimonas, Peptostreptococcus, Prevotella, and Fusobacterium species had important roles in discriminating the D group from the other 2 groups.

CONCLUSION

These results suggest differences in the microbial community composition among DSs, normal-healing sockets, and post-treated sockets. These results provide better insight into the development of DS and enhance the understanding of DS. Nonetheless, further studies are necessary to investigate and confirm how these differential bacteria contribute to the development of the disease.

Discovery of a Novel Periodontal Disease-Associated Bacterium

One of the world's most common infectious disease, periodontitis (PD), derives from largely uncharacterized communities of oral bacteria growing as biofilms (a.k.a. plaque) on teeth and gum surfaces in periodontal pockets. Bacteria associated with periodontal disease trigger inflammatory responses in immune cells, which in later stages of the disease cause loss of both soft and hard tissue structures supporting teeth. Thus far, only a handful of bacteria have been characterized as infectious agents of PD. Although deep sequencing technologies, such as whole community shotgun sequencing have the potential to capture a detailed picture of highly complex bacterial communities in any given environment, we still lack major reference genomes for the oral microbiome associated with PD and other diseases. In recent work, by using a combination of supervised machine learning and genome assembly, we identified a genome from a novel member of the Bacteroidetes phylum in periodontal samples. Here, by applying a comparative metagenomics read-classification approach, including 272 metagenomes from various human body sites, and our previously assembled draft genome of the uncultivated Candidatus Bacteroides periocalifornicus (CBP) bacterium, we show CBP's ubiquitous distribution in dental plaque, as well as its strong association with the well-known pathogenic "red complex" that resides in deep periodontal pockets.

Periodontitis: facts, fallacies and the future

This volume of Periodontology 2000 represents the 25th anniversary of the Journal, and uses the occasion to assess important advancements in periodontology over the past quarter-century as well as the hurdles that remain. Periodontitis is defined by pathologic loss of the periodontal ligament and alveolar bone. The disease involves complex dynamic interactions among active herpesviruses, specific bacterial pathogens and destructive immune responses. Periodontal diagnostics is currently based on clinical rather than etiologic criteria, and provides limited therapeutic guidance. Periodontal causative treatment consists of scaling, antiseptic rinses and occasionally systemic antibiotics, and surgical intervention has been de-emphasized, except perhaps for the most advanced types of periodontitis. Plastic surgical therapy includes soft-tissue grafting to cover exposed root surfaces and bone grafting to provide support for implants. Dental implants are used to replace severely diseased or missing teeth, but implant overuse is of concern. The utility of laser treatment for periodontitis remains unresolved. Host modulation and risk-factor modification therapies may benefit select patient groups. Patient self-care is a critical part of periodontal health care, and twice-weekly oral rinsing with 0.10-0.25% sodium hypochlorite constitutes a valuable adjunct to conventional anti-plaque and anti-gingivitis treatments. A link between periodontal herpesviruses and systemic diseases is a strong biological plausibility. In summary, research during the past 25 years has significantly changed our concepts of periodontitis pathobiology and has produced more-effective and less-costly therapeutic options.

Oral microbiota of periodontal health and disease and their changes after nonsurgical periodontal therapy

This study examined the microbial diversity and community assembly of oral microbiota in periodontal health and disease and after nonsurgical periodontal treatment. The V4 region of 16S rRNA gene from DNA of 238 saliva and subgingival samples of 21 healthy and 48 diseased subjects was amplified and sequenced. Among 1979 OTUs identified, 28 were overabundant in diseased plaque. Six of these taxa were also overabundant in diseased saliva. Twelve OTUs were overabundant in healthy plaque. There was a trend for disease-associated taxa to decrease and health-associated taxa to increase after treatment with notable variations among individual sites. Network analysis revealed modularity of the microbial communities and identified several health- and disease-specific modules. Ecological drift was a major factor that governed community turnovers in both plaque and saliva. Dispersal limitation and homogeneous selection affected the community assembly in plaque, with the additional contribution of homogenizing dispersal for plaque within individuals. Homogeneous selection and dispersal limitation played important roles, respectively, in healthy saliva and diseased pre-treatment saliva between individuals. Our results revealed distinctions in both taxa and assembly processes of oral microbiota between periodontal health and disease. Furthermore, the community assembly analysis has identified potentially effective approaches for managing periodontitis.

Do we treat our patients or rather periodontal microbes with adjunctive antibiotics in periodontal therapy? A 16S rDNA microbial community analysis

Empiric antibiotics are often used in combination with mechanical debridement to treat patients suffering from periodontitis and to eliminate disease-associated pathogens. Until now, only a few next generation sequencing 16S rDNA amplicon based publications with rather small sample sizes studied the effect of those interventions on the subgingival microbiome. Therefore, we studied subgingival samples of 89 patients with chronic periodontitis (solely non-smokers) before and two months after therapy. Forty-seven patients received mechanical periodontal therapy only, whereas 42 patients additionally received oral administered amoxicillin plus metronidazole (500 and 400 mg, respectively; 3x/day for 7 days). Samples were sequenced with Illumina MiSeq 300 base pairs paired end technology (V3 and V4 hypervariable regions of the 16S rDNA). Inter-group differences before and after therapy of clinical variables (percentage of sites with pocket depth ≥ 5mm, percentage of sites with bleeding on probing) and microbiome variables (diversity, richness, evenness, and dissimilarity) were calculated, a principal coordinate analysis (PCoA) was conducted, and differential abundance of agglomerated ribosomal sequence variants (aRSVs) classified on genus level was calculated using a negative binomial regression model. We found statistically noticeable decreased richness, and increased dissimilarity in the antibiotic, but not in the placebo group after therapy. The PCoA revealed a clear compositional separation of microbiomes after therapy in the antibiotic group, which could not be seen in the group receiving mechanical therapy only. This difference was even more pronounced on aRSV level. Here, adjunctive antibiotics were able to induce a microbiome shift by statistically noticeably reducing aRSVs belonging to genera containing disease-associated species, e.g., Porphyromonas, Tannerella, Treponema, and Aggregatibacter, and by noticeably increasing genera containing health-associated species. Mechanical therapy alone did not statistically noticeably affect any disease-associated taxa. Despite the difference in microbiome modulation both therapies improved the tested clinical parameters after two months. These results cast doubt on the relevance of the elimination and/or reduction of disease-associated taxa as a main goal of periodontal therapy.

The oral microbiome - an update for oral healthcare professionals

For millions of years, our resident microbes have coevolved and coexisted with us in a mostly harmonious symbiotic relationship. We are not distinct entities from our microbiome, but together we form a 'superorganism' or holobiont, with the microbiome playing a significant role in our physiology and health. The mouth houses the second most diverse microbial community in the body, harbouring over 700 species of bacteria that colonise the hard surfaces of teeth and the soft tissues of the oral mucosa. Through recent advances in technology, we have started to unravel the complexities of the oral microbiome and gained new insights into its role during both health and disease. Perturbations of the oral microbiome through modern-day lifestyles can have detrimental consequences for our general and oral health. In dysbiosis, the finely-tuned equilibrium of the oral ecosystem is disrupted, allowing disease-promoting bacteria to manifest and cause conditions such as caries, gingivitis and periodontitis. For practitioners and patients alike, promoting a balanced microbiome is therefore important to effectively maintain or restore oral health. This article aims to give an update on our current knowledge of the oral microbiome in health and disease and to discuss implications for modern-day oral healthcare.

Statistical models and computational algorithms for discovering relationships in microbiome data

Microbiomes, populations of microscopic organisms, have been found to be related to human health and it is expected further investigations will lead to novel perspectives of disease. The data used to analyze microbiomes is one of the newest types (the result of high-throughput technology) and the means to analyze these data is still rapidly evolving. One of the distributions that have been introduced into the microbiome literature, the Dirichlet-Multinomial, has received considerable attention. We extend this distribution's use uncover compositional relationships between organisms at a taxonomic level. We apply our new method in two real microbiome data sets: one from human nasal passages and another from human stool samples.

A microbial survey of the International Space Station (ISS)

BACKGROUND

Modern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station (ISS). This ISS sampling involved the collection and microbial analysis (via 16S rDNA PCR) of 15 surfaces sampled by swabs onboard the ISS. This sampling was a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS). Learning more about the microbial inhabitants of the "buildings" in which we travel through space will take on increasing importance, as plans for human exploration continue, with the possibility of colonization of other planets and moons.

RESULTS

Sterile swabs were used to sample 15 surfaces onboard the ISS. The sites sampled were designed to be analogous to samples collected for (1) the Wildlife of Our Homes project and (2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rDNA genes amplified from DNA extracted from each swab was used to produce a census of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both homes on Earth and data from the Human Microbiome Project.

CONCLUSIONS

While significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the ISS was more similar to home surfaces than to the human microbiome samples. The ISS surfaces are species-rich with 1,036-4,294 operational taxonomic units (OTUs per sample). There was no discernible biogeography of microbes on the 15 ISS surfaces, although this may be a reflection of the small sample size we were able to obtain.