Subgingival Microbiome Research Articles

Comparative evaluation of changes in the periodontal microbiome in patients with chronic generalized periodontitis after Vector-therapy

Relevance. The development and implementation into wide clinical practice an effective methods for removing subgingival biofilms, which allow qualitatively removing periodontopathogens and preserving the structure of the root surface for the subsequent restoration of the supporting-retaining apparatus of the tooth, is an important aspect in the treatment of chronic generalized periodontitis. Purpose. To evaluate the effectiveness of removing microbial biofilm in patients with chronic generalized periodontitis using Vector-therapy in comparison with hand-held instruments. Materials and methods . The study involved 119 patients (68 women and 51 men) in the age of 26-70 years (mean age 47.0 ± 12.5 years) with chronic generalized periodontitis of moderate and severe degree. The patients were divided into 3 groups depending on the method of root surface treatment (Curettes, Vector Paro, combined Curette Vector Paro treatment). Patients of all groups was evaluated such parameters, as BOP, PD / HPA, CAL / RFP and radiological parameters. For microbiological examination, real-time PCR was used with the sampling of the contents of the periodontal pocket before treatment for 10 days and 6 weeks. The dynamics of clinical indicators, frequency of occurrence, absolute, and the participation of key periodontal pathogenic microorganisms (A. actinomycetemcomitans, P. Gingivalis, P. intermedia, T. forsythia, T. denticola) and Candida albicans from the total bacterial mass of the contents of the periodontal pocket were assessed. The results were processed statistically using the Statistica software. Results. When comparing the groups with each other, a statistically significant relationship was found for a decrease in PB in group 2 (Vector) and group 3 (Curettes Vector Paro) in group 1 (Curettes), an inverse correlation between the level of bleeding (BOR) at a follow-up of 10 days (rs -0.463, p < 0.001) and 6 weeks (rs -0.342, p-value 0.025) and by the method of removing subgingival dental plaque. Statistically significant changes in the frequency of occurrence, number and proportion of periodontal pathogenic microorganisms in the groups were found in the dynamics of observation, indicating changes in the structure of the subgingival microbiome. Conclusion. The inclusion of Vector therapy in conservative treatment significantly accelerates the timing of inflammation in the periodontal tissues and leads to some significant shifts in the structure of the subgingival microbiome.

Subgingival microbiome and clinical periodontal status in an elderly cohort: The WHICAP ancillary study of oral health.

There is a sparsity of data describing the periodontal microbiome in elderly individuals. We analyzed the association of subgingival bacterial profiles and clinical periodontal status in a cohort of participants in the Washington Heights-Inwood Columbia Aging Project (WHICAP). Dentate individuals underwent a full-mouth periodontal examination at six sites/tooth. Up to four subgingival plaque samples per person, each obtained from the mesio-lingual site of the most posterior tooth in each quadrant, were harvested and pooled. Periodontal status was classified according to the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) criteria as well as based on the percentage of teeth/person with pockets ≥4mm deep. Bacterial DNA was isolated and was processed and analyzed using Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS). Differential abundance across the periodontal phenotypes was calculated using the R package DESeq2. α- and β-diversity metrics were calculated using DADA2-based clustering. The mean age of the 739 participants was 74.5 years, and 32% were male. Several taxa including Sneathia amnii-like sp., Peptoniphilaceae [G-1] bacterium HMT 113, Porphyromonas gingivalis, Fretibacterium fastidiosum, Filifactor alocis, and Saccharibacteria (TM7) [G-1] bacterium HMT 346 were more abundant with increasing severity of periodontitis. In contrast, species such as Veillonella parvula, Veillonella dispar, Rothia dentocariosa, and Lautropia mirabilis were more abundant in health. Microbial diversity increased in parallel with the severity and extent of periodontitis. The observed subgingival bacterial patterns in these elderly individuals corroborated corresponding findings in younger cohorts and were consistent with the concept that periodontitis is associated with perturbations in the resident microbiome.

Subgingival microflora in adolescent females with polycystic ovary syndrome and its association with oral hygiene, gingivitis, and selected metabolic and hormonal parameters

ObjectivesResearch studies suggest that polycystic ovary syndrome (PCOS) may influence the composition of the oral microflora in women. This study aimed to investigate factors affecting the number of selected periopathogens in a young cohort of females with PCOS and to assess the association between oral hygiene, subgingival microbiome, gingival health, and metabolic and hormonal parameters.Materials and methodsThirty-two subjects with PCOS and twenty-three healthy controls aged 15–19 years were examined periodontally by a calibrated dentist. A real-time PCR method was used for the identification of 9 subgingival microorganisms. Subjects with PCOS underwent blood tests for determination of FSH, LH, total testosterone, DHEA-S, estradiol, SHBG, fasting glucose, fasting insulin, and lipid profile.ResultsGingival index (GI), the proportion of bleeding sites (BOP%), probing depth (PD), and plaque index (PLI) did not differ significantly between cases and healthy age-mates. The control group had significantly higher levels of Peptostreptococcus micros and substantially greater percentage of subjects infected by Treponema denticola. Capnocytophaga gingivalis count was positively correlated with the level of estradiol, while the concentration of HDL-C was negatively correlated with the number of Aggregatibacter actinomycetemcomitans and orange complex bacteria.ConclusionsPCOS in young patients was not associated with higher pathogenicity of subgingival biofilms.Clinical relevanceFurther studies are needed to explain the relationship between hormonal and metabolic abnormalities, subgingival microflora, and periodontal health in patients with PCOS.

Microbial Profile During Pericoronitis and Microbiota Shift After Treatment.

The microflora of the distal pocket is considered as the major cause of pericoronitis. How the oral microflora changes during pericoronitis and whether different types of impacted third molar harbor the same microflora are still unknown. Saliva, subgingival plaque, and gingival plaque of mandibular third molars (M3Ms) were collected from twelve patients with acute pericoronitis. They were given local irrigation or local irrigation + antibiotics according to symptoms. Samples were harvested at the first visit with pericoronitis, 1 week after treatment, and 6 weeks after treatment. 16S rRNA gene polymerase chain reaction products were generated and sequenced after DNA isolation. Comparison of three sampling sites showed that, the subgingival plaque of M3Ms had most remarkable changes in symptomatic period, including a significant increase in microbial richness, and a convergent trend in microbial composition. After treatment, the subgingival microbiome was altered and largely returned to the state in asymptomatic period. In summary, the distal subgingival microbiota of M3M was most likely to be associated with the pathogenesis of pericoronitis. The post-treatment microbiota shift of M3M proved the effectiveness of treatment. The inclination type of impacted M3Ms and treatment method would also make a difference to the pericoronal microbiota.

The Subgingival Microbiome in Patients with Down Syndrome and Periodontitis

Objective: To describe the subgingival microbiome of individuals with Down syndrome (DS). Methods: We conducted a cross-sectional observational study that obtained bacterial DNA samples from 50 patients with DS, 25 with periodontitis (PDS) and 25 with a healthy periodontal condition (HDS). The samples were analyzed by sequencing the 16S rRNA gene V3–V4 hypervariable region using the MiSeq System. Taxonomic affiliations were assigned using the naïve Bayesian classifier integrated in QIIME2 plugins. We evaluated the difference in bacteria abundance between the sample groups using Wilcoxon and Kruskal–Wallis tests. We evaluated the alpha diversity of the identified species using the Observed, Chao1metric, ACE and Shannon indices and evaluated beta diversity with principal coordinate analysis (registration code: 2018/510). Results: Twenty-one genera and 39 bacterial species showed a significantly different abundance between the study groups. Among the genera, Porphyromonas, Treponema, Tannerella and Aggregatibacter were more abundant in the PDS group than in the HDS group, as were the less commonly studied Filifactor, Fretibacterium and Desulfobulbus genera. Among the species, Porphyromonas spp. and Tannerella spp. were the most abundant in the PDS group; the most abundant species in the HDS group were Pseudomonas spp., Granulicatella spp. and Gemella spp. Conclusion: Well-recognized periodontal pathogens and newly proposed pathogenic taxa were associated with periodontitis in patients with DS.

Well-maintained patients with a history of periodontitis still harbor a more dysbiotic microbiome than health.

It remains unclear whether well-maintained subjects, with periodontitis in the past, effectively treated, and maintained for a long time, have the same subgingival microbiome as healthy subjects. Therefore, the objective of this study was to investigate the characteristics of the subgingival microbiome in well-maintained patients with a history of periodontitis compared with healthy subjects. We recruited in 17 well-maintained individuals (no evidence of clinical inflammation and progress of periodontitis) and 21 healthy individuals. Periodontal clinical parameters, consisting of missing teeth, plaque index (PLI), periodontal depth (PD), and bleeding index (BI), were recorded and analyzed. The pooled subgingival samples from mesiobuccal sites of two maxillary first molars were collected. The V3-V4 region of 16S rRNA gene from 38 subgingival samples was sequenced and analyzed. Alpha diversity, microbial composition, types of bacteria, functional pathways between well-maintained group and health group were compared using Mann-Whitney U test. Spearman correlation was used in analyzing the symbiotic relationship among taxa. A classification model was constructed to distinguish two ecological types. The maintained individuals demonstrated a different microbiome from healthy subjects, with higher diversity, more disordered structure, more pathogenic microbiota, and more host-destructive metabolism pathways. The genera Actinomyces, Streptococcus, Leptotrichia, Capnocytophaga, Lautropia, and Fusobacterium were predominant components with relative abundance >5% in the subgingival microbiome of well-maintained patients. The classification model by microbiota got a remarkable accuracy of 83.33%. Individuals with well-maintained periodontitis showed a more dysbiotic microbial community than healthy individuals. Therefore, close monitoring and scheduled maintenance treatment are necessary for them to maintain a healthy periodontal condition.

Aggregatibacter Actinomycetemcomitans Induces Autophagy in Human Junctional Epithelium Keratinocytes.

The adverse environmental conditions found in the periodontium during periodontitis pathogenesis stimulate local autophagy responses, mainly due to a continuous inflammatory response against the dysbiotic subgingival microbiome. The junctional epithelium represents the main site of the initial interaction between the host and the dysbiotic biofilm. Here, we investigated the role of autophagy in junctional epithelium keratinocytes (JEKs) in response to Aggregatibacter actinomycetemcomitans or its purified lipopolysaccharides (LPS). Immunofluorescence confocal analysis revealed an extensive nuclear translocation of transcription factor EB (TFEB) and consequently, an increase in autophagy markers and LC3-turnover assessed by immunoblotting and qRT-PCR. Correspondingly, challenged JEKs showed a punctuate cytosolic profile of LC3 protein contrasting with the diffuse distribution observed in untreated controls. Three-dimensional reconstructions of confocal images displayed a close association between intracellular bacteria and LC3-positive vesicles. Similarly, a close association between autophagic vesicles and the protein p62 was observed in challenged JEKs, indicating that p62 is the main adapter protein recruited during A. actinomycetemcomitans infection. Finally, the pharmacological inhibition of autophagy significantly increased the number of bacteria-infected cells as well as their death, similar to treatment with LPS. Our results indicate that A. actinomycetemcomitans infection induces autophagy in JEKs, and this homeostatic process has a cytoprotective effect on the host cells during the early stages of infection.

Significant Short-Term Shifts in the Microbiomes of Smokers With Periodontitis After Periodontal Therapy With Amoxicillin & Metronidazole as Revealed by 16S rDNA Amplicon Next Generation Sequencing.

The aim of this follow-up study was, to compare the effects of mechanical periodontal therapy with or without adjunctive amoxicillin and metronidazole on the subgingival microbiome of smokers with periodontitis using 16S rDNA amplicon next generation sequencing. Fifty-four periodontitis patients that smoke received either non-surgical periodontal therapy with adjunctive amoxicillin and metronidazole (n = 27) or with placebos (n = 27). Subgingival plaque samples were taken before and two months after therapy. Bacterial genomic DNA was isolated and the V4 hypervariable region of the bacterial 16S rRNA genes was amplified. Up to 96 libraries were normalized and pooled for Illumina MiSeq paired-end sequencing with almost fully overlapping 250 base pairs reads. Exact ribosomal sequence variants (RSVs) were inferred with DADA2. Microbial diversity and changes on the genus and RSV level were analyzed with non-parametric tests and a negative binomial regression model, respectively. Before therapy, the demographic, clinical, and microbial parameters were not significantly different between the placebo and antibiotic groups. Two months after the therapy, clinical parameters improved and there was a significantly increased dissimilarity of microbiomes between the two groups. In the antibiotic group, there was a significant reduction of genera classified as Porphyromonas, Tannerella, and Treponema, and 22 other genera also decreased significantly, while Selenomonas, Capnocytophaga, Actinomycetes, and five other genera significantly increased. In the placebo group, however, there was not a significant decrease in periodontal pathogens after therapy and only five other genera decreased, while Veillonella and nine other genera increased. We conclude that in periodontitis patients who smoke, microbial shifts occurred two months after periodontal therapy with either antibiotics or placebo, but genera including periodontal pathogens decreased significantly only with adjunctive antibiotics.

Zero-inflated Poisson factor model with application to microbiome read counts.

Dimension reduction of high-dimensional microbiome data facilitates subsequent analysis such as regression and clustering. Most existing reduction methods cannot fully accommodate the special features of the data such as count-valued and excessive zero reads. We propose a zero-inflated Poisson factor analysis model in this paper. The model assumes that microbiome read counts follow zero-inflated Poisson distributions with library size as offset and Poisson rates negatively related to the inflated zero occurrences. The latent parameters of the model form a low-rank matrix consisting of interpretable loadings and low-dimensional scores that can be used for further analyses. We develop an efficient and robust expectation-maximization algorithm for parameter estimation. We demonstrate the efficacy of the proposed method using comprehensive simulation studies. The application to the Oral Infections, Glucose Intolerance, and Insulin Resistance Study provides valuable insights into the relation between subgingival microbiome and periodontaldisease.

Analysis of subgingival microbiome of periodontal disease and rheumatoid arthritis in Chinese: A case-control study.

ObjectivePeriodontitis (PD) and rheumatoid arthritis (RA) share similar pathogenesis. Evidences indicated that oral bacteria play an important role in the etiology of both diseases. For example, Porphyromonas gingvialis connect the two diseases through immune responses. We designed this study to compare bacterial diversity in RA, PD and healthy subjects and to investigate whether there are other oral bacteria play an potential role in linking the two diseases.MethodsThis study included 3 groups of Chinese participants who visited Sichuan Provincial People’s Hospital during August 2018 and March 2019. Subgingival plaques were collected from RA group (n = 54), PD group (n = 45) and normal group (n = 44). Illumina MiSeq was used to compare the composition of subgingival microbiota and analyze correlations between oral bacteria and both diseases.ResultsAlpha diversity Analysis reflected similar microbiome profile in RA, PD and healthy groups. But we found Treponema was significantly more abundant in the PD and RA groups than healthy group at each taxonomic level from the phylum down to the genus level. Porphyromonas, Prevotella, and Veilonella were significantly more abundant in RA while Streptococcus, Gemella, Planobacterium were verified the opposite results.ConclusionsWe found no significant group differences referent to either microbial diversity or richness. But we picked out Spirochaetes which may link the two diseases. Upper/lower regulation of some microbia in RA may remind us a direction to explore the role they play in pathogenesis.

Modeling Normal and Dysbiotic Subgingival Microbiomes: Effect of Nutrients

Screening for microbiome modulators requires availability of a high-throughput in vitro model that replicates subgingival dysbiosis and normobiosis, with a tool to measure microbial dysbiosis. Here, we tested various formulations to grow health- and periodontitis-associated subgingival microbiomes in parallel, and we describe a new subgingival dysbiosis index. Subgingival plaque samples pooled from 5 healthy subjects and, separately, 5 subjects with periodontitis were used to inoculate a Calgary Biofilm Device containing saliva-conditioned, hydroxyapatite-coated pegs. Microbiomes were grown for 7 d on either nutrient-rich media—including a modification of SHI medium, brain-heart infusion (BHI) supplemented with hemin and vitamin K, and a blend of SHI and BHI, each at 3 sucrose concentrations (0%, 0.05% and 0.1%)—or nutrient-limited media (saliva with 5%, 10%, or 20% inactivated human serum). The microbiomes were assessed for biomass, viability, and 16S rRNA profiles. In addition to richness and diversity, a dysbiosis index was calculated as the ratio of the sum of relative abundances of disease-associated species to that of health-associated species. The supplemented BHI and blend of SHI and BHI resulted in the highest biomass, whereas saliva-serum maximized viability. Distinct groups of bacteria were enriched in the different media. Regardless of medium type, the periodontitis-derived microbiomes showed higher species richness and alpha diversity and clustered with their inoculum separate from the health-derived microbiomes. Microbiomes grown in saliva-serum showed the highest species richness and the highest similarity to the clinical inocula in both health and disease. However, inclusion of serum reduced alpha diversity and increased dysbiosis in healthy microbiomes in a dose-dependent manner, mainly due to overenrichment of Porphyromonas species. The modification of SHI stood second in terms of species richness and diversity but resulted in low biomass and viability and significantly worsened dysbiosis in the periodontitis-derived microbiomes. Overall, saliva with 5% human serum was optimal for replicating subgingival microbiomes from health and disease.

Loss of the disease-associated glycosyltransferase Galnt3 alters Muc10 glycosylation and the composition of the oral microbiome

Loss of the disease-associated glycosyltransferase Galnt3 alters Muc10 glycosylation and the composition of the oral microbiome

Composition and diversity of the subgingival microbiome and its relationship with age in postmenopausal women: an epidemiologic investigation

BackgroundThe extent to which the composition and diversity of the oral microbiome varies with age is not clearly understood.MethodsThe 16S rRNA gene of subgingival plaque in 1219 women, aged 53–81 years, was sequenced and its taxonomy annotated against the Human Oral Microbiome Database (v.14.5). Composition of the subgingival microbiome was described in terms of centered log(2)-ratio (CLR) transformed OTU values, relative abundance, and prevalence. Correlations between microbiota abundance and age were evelauted using Pearson Product Moment correlations. P-values were corrected for multiple testing using the Bonferroni method.ResultsOf the 267 species identified overall, Veillonella dispar was the most abundant bacteria when described by CLR OTU (mean 8.3) or relative abundance (mean 8.9%); whereas Streptococcus oralis, Veillonella dispar and Veillonella parvula were most prevalent (100%, all) when described as being present at any amount. Linear correlations between age and several CLR OTUs (Pearson r = − 0.18 to 0.18), of which 82 (31%) achieved statistical significance (P < 0.05). The correlations lost significance following Bonferroni correction. Twelve species that differed across age groups (each corrected P < 0.05); 5 (42%) were higher in women ages 50–59 compared to ≥70 (corrected P < 0.05), and 7 (48%) were higher in women 70 years and older.ConclusionsWe identified associations between several bacterial species and age across the age range of postmenopausal women studied. Understanding the functions of these bacteria could identify intervention targets to enhance oral health in later life.

Host-Microbial Interactions in Systemic Lupus Erythematosus and Periodontitis.

Background: Systemic lupus erythematosus (SLE) is a potentially fatal complex autoimmune disease, that is characterized by widespread inflammation manifesting tissue damage and comorbidities across the human body including heart, blood vessels, joints, skin, liver, kidneys, and periodontal tissues. The etiology of SLE is partially attributed to a deregulated inflammatory response to microbial dysbiosis and environmental changes. In the mouth, periodontal environment provides an optimal niche for local and systemic inflammation. Our aim was to evaluate the reciprocal impact of periodontal subgingival microbiome on SLE systemic inflammation.Methods: Ninety-one female subjects were recruited, including healthy (n = 31), SLE-inactive (n = 29), and SLE-active (n = 31). Patients were screened for probing depth, bleeding on probing, clinical attachment level, and classified according to CDC/AAP criteria with or without periodontal dysbiosis. Serum inflammatory cytokines were measured by human cytokine panel and a targeted pathogenic subgingival biofilm panel was examined by DNA-DNA checkerboard from subgingival plaque samples.Results: The results showed significant upregulation of serum proinflammatory cytokines in individuals with SLE when compared to controls. Stratification of subject's into SLE-inactive (I) and SLE-active (A) phenotypes or periodontitis and non-periodontitis groups provided new insights into SLE pathophysiology. Ten proinflammatory cytokines were upregulated in serum of SLE-I only and one in SLE-A only. Four molecules overlapped in SLE-A and SLE-I. Anti-inflammatory cytokines included IL-4 IL-10, which were upregulated in SLE-I sera (but not SLE-A), controlling clinical phenotypes. Out of 24 significant differential oral microbial abundances found in SLE, 14 unique subgingival bacteria profiles were found to be elevated in SLE. The most severe oral pathogens (Treponema denticola and Tannerella forsythia) showed increase abundances on SLE-A periodontal sites when compared to SLE-I and healthy controls. Inflammation as measured by cytokine-microbial correlations showed that periodontal pathogens dominating the environment increased proinflammatory cytokines systemically.Conclusions: Altogether, low-grade systemic inflammation that influenced SLE disease activity and severity was correlated to dysbiotic changes of the oral microbiota present in periodontal diseases.

Pyrosequencing of the subgingival microbiome in peri-implantitis after non-surgical mechanical debridement therapy.

Peri-implantitis remains a challenge for dental implant therapy, and the prognosis of non-surgical therapy for peri-implantitis is unsatisfactory. In order to reveal the impact of non-surgical mechanical debridement therapy on microbial communities, we investigated the subgingival microbial communities of healthy implants and implants with peri-implantitis, both before and after the therapy. Subgingival plaques were collected from patients with healthy dental implants (HC; n=10) and from patients with peri-implantitis (n=13) before and after non-surgical mechanical debridement therapy. The treatment was conducted using curettes for submucosal debridement followed by irrigation with 0.2% (w/v) chlorhexidine, with re-examination 1month later. 16S rRNA pyrosequencing was used to analyze the subgingival microbiome, and co-occurrence networks were adopted to explore the interactions between pathogens in the microbial communities. A total of 506955 high-quality reads were generated, and 2222 operational taxonomic units were finally detected using a 97% similarity cutoff, with a mean of 249±69 per sample. The peri-implantitis sites harbored similar microbial communities before and after the treatment, as demonstrated by the microbial diversity, relative abundance, and prevalence of bacteria. Most importantly, the microbial community structures were stable before and after non-surgical therapy based on the microbial diversity and bacterial composition, as well as the interactions between key pathogens, including Enterobacteriaceae, Selenomonas sputigena, Parvimonas, Eubacterium infirmum, Campylobacter gracilis, Tannerella forsythia, and Fusobacterium, which were measured using a co-occurrence network analysis. Periodontal pathogens were also detected in subgingival plaque after the treatment. Distinct microbial communities were found between the healthy and peri-implantitis sites. Our results demonstrate that non-surgical mechanical debridement therapy did not significantly affect the subgingival microbial communities in peri-implantitis, and the stable microbial networks created via interactions among pathogens may be responsible for the poor prognosis of peri-implantitis treatment.

The subgingival microbiome associated with periodontitis in type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) is a systemic disease, predisposing patients to other inflammatory conditions including periodontitis. The subgingival microbiome, a key player in periodontitis pathogenesis, is not well characterized in T2DM population. To better understand whether the subgingival microbiome is different between T2DM and systemically healthy, nondiabetic (ND) subjects, we performed a longitudinal analysis of the subgingival microbiome in T2DM patients (n = 15) compared with ND subjects (n = 16). Using metagenomic shotgun sequencing, we investigated the microbiome in the healthy periodontal state, periodontitis state, and resolved state after treatment. We found that in the periodontitis state, the shift in the subgingival microbiome from the healthy state was less prominent in T2DM compared with ND subjects, yet the clinical signs of disease were similar for both. Furthermore, we revealed highly correlated presence of pathogenic species in relative abundance not only in the periodontitis state, but also in the healthy state in T2DM, suggesting an elevated risk of progression to periodontitis in this cohort. We further investigated the functional potentials of the subgingival microbiome and identified a set of microbial marker genes associated with the clinical states. These genes were significantly enriched in 21 pathways, some of which are associated with periodontitis and some potentially link T2DM and periodontitis. This study identified the longitudinal changes of the subgingival microbiome associated with periodontitis in T2DM and suggests that T2DM patients are more susceptible to shifts in the subgingival microbiome toward dysbiosis, potentially due to impaired host metabolic and immune regulation.

Searching Deep and Wide: Advances in the Molecular Understanding of Dental Caries and Periodontal Disease.

During the past decades, remarkable progress has been made in the understanding of the molecular basis of the 2 most common oral diseases, dental caries and periodontal disease. Improvements in our knowledge of the diseases' underlying biology have illuminated previously unrecognized aspects of their pathogenesis. Importantly, the key role of the oral (supragingival and subgingival) microbiome is now well recognized, and both diseases are now best understood as dysbiotic. From a host susceptibility standpoint, some progress has been made in dissecting the "hyperinflammatory" trait and other pathways of susceptibility underlying periodontitis, and novel susceptibility loci have been reported for dental caries. Nevertheless, there is a long road to the translation of these findings and the realization of precision oral health. There is promise and hope that the rapidly increasing capacity of generating multiomics data layers and the aggregation of study samples and cohorts comprising thousands of participants will accelerate the discovery and translation processes. A first key element in this process has been the identification and interrogation of biologically informed disease traits-these "deep" or "precise" traits have the potential of revealing biologically homogeneous disease signatures and genetic susceptibility loci that might present with overlapping or heterogeneous clinical signs. A second key element has been the formation of international consortia with the goals of combining and harmonizing oral health data of thousands of individuals from diverse settings-these "wide" collaborative approaches leverage the power of large sample sizes and are aimed toward the discovery or validation of genetic influences that would otherwise be impossible to detect. Importantly, advancements via these directions require an unprecedented engagement of systems biology and team science models. The article highlights novel insights into the molecular basis of dental caries and chronic periodontitis that have been gained from recent and ongoing studies involving "deep" and "wide" analytical approaches.

Short-term effects of hyaluronic acid on the subgingival microbiome in peri-implantitis: A randomized controlled clinical trial.

The aim of our study was to evaluate the effects of a hyaluronic acid (HA) gel at 45 days on the microbiome of implants with peri-implantitis with at least 1 year of loading. A randomized controlled trial was conducted in peri-implantitis patients. Swabs containing the samples were collected both at baseline and after 45 days of treatment. 16S rRNA sequencing techniques were used to investigate the effect of HA gel on the subgingival microbiome. One hundred and eight samples of 54 patients were analyzed at baseline and after follow-up at 45 days. Three strata with different microbial composition were obtained in the samples at baseline, representing three main microbial consortia associated with peri-implantitis. Stratum 1 did not show any difference for any variable after treatment with HA, whereas in stratum 2, Streptococcus, Veillonella, Rothia, and Granulicatella did decrease (P< 0.05). Similarly, Prevotella and Campylobacter (P< 0.05) decreased in stratum 3 after treatment with HA. Microbial diversity was found to be decreased in stratum 3 (P< 0.05) after treatment with HA compared with the control group, in which an increase was found (P< 0.05). HA reduced the relative abundance of peri-implantitis-related microorganisms, especially the early colonizing bacteria, suggesting a specific action during the first stages in the development of the disease. HA did not alter relative abundances of non-oral genera. The use of HA in advanced stages of peri-implantitis resulted in a decrease in microbial alpha diversity, suggesting a protective action of the peri-implant site against bacteria colonization.

The effect of the octenidine-based oral antiseptic on the structure of microbial communities and periodontal status in patients with fixed orthodontic treatments.

To evaluate the effect of an octenidine (OCT)-based antiseptic on the gingival inflammation and microbial composition of subgingival dental plaque in patients with fixed orthodontic appliances. Thirty-three orthodontic patients were randomized into 2 groups. The control group patients were given standard oral hygiene and dietary advice, while the experimental group patients used an OCT-based antiseptic together with standard oral hygiene and dietary recommendations. The periodontal status was evaluated using the following indices: the plaque index (PI), the gingival index (GI), the papilla bleeding index (PBI) and the probing pocket depth (PD). Next Generation Sequencing of the 16S rRNA amplicons was performed in order to assess the subgingival microbiome. The PD values obtained were significantly lower in the experimental group after one month, as well as PBI. The microbiological analysis showed a significant increase in the occurrence of the genus Prevotella in the control group, while the number of other periodontopathogens remained stable in both groups. The changes in the abundance of the bacteria not directly associated with periodontal disease were also observed. The use of an OCT-based antiseptic has a positive effect on the prevention of gingival inflammation. Additionally, it also prevents a likely increase in numbers of periodontopathogens of the subgingival dental plaque in the first three months of fixed orthodontic treatment.

Microbiome in maintained periodontitis and its shift over a single maintenance interval of 3months.

To assess the subgingival microbial shift of maintained periodontitis treated by ultrasonic scaling (US) or air polishing (AP) during a 3-month maintenance interval. We conducted a 12-week randomized split-mouth controlled trial with US and AP in 17 maintained subjects (bleeding on probing [BOP%] ≤25%, probing depth [PD] ≤5mm). They were monitored at baseline, week 2, week 8 and week 12. The V3-V4 region of the 16S rDNA from 136 subgingival plaque samples was sequenced and analysed. Treatment by US or AP could effectively reduce the PD, microbial richness, diversity, periodontitis-associated microbiota and pathogenic metabolism in maintained periodontitis. Bacteria recolonized after treatment and returned to the pre-treatment level 12weeks after treatment. Ultrasonic scaling group demonstrated slight advantage in reducing BOP (%), pathogenic bacteria and metabolism than AP group. Pathogenic microbiota and commensal microbiota kept a balance in subgingival community of maintained patients during the 3-month interval. Treatment by US or AP effectively reduced the pathogenicity of subgingival microbiome by reducing microbial diversity, proportion of periodontitis-associated microbiota and pathogenic metabolism. It helped to keep a balanced subgingival community and stable periodontal condition over a single maintenance interval of 3months.