Intraindividual variation in core microbiota in peri-implantitis and periodontitis

Microbiome of periodontitis and peri-implantitis before and after therapy: Long-read 16S rRNA gene amplicon sequencing

AIMS

The microbial profiles of peri-implantitis and periodontitis (PT) are inconclusive. The controversies mainly arise from the differences in sampling sites, targeted gene fragment, and microbiome analysis techniques. The objective of this study was to explore the microbiomes of peri-implantitis (PI), control implants (CI), PT and control teeth (CT), and the microbial change of PI after nonsurgical treatment (PIAT).

METHODS

Twenty-two patients diagnosed with both PT and peri-implantitis were recruited. Clinical periodontal parameters and radiographic bone levels were recorded. In each patient, the subgingival and submucosal plaque samples were collected from sites with PI, CI, PT, CT, and PIAT. Microbiome diversity was analyzed by high-throughput amplicon sequencing using full-length of 16S rRNA gene by next generation sequencing.

RESULTS

The 16S rRNA gene sequencing analysis revealed 512 OTUs in oral microbiome and 377 OTUs reached strain levels. The PI and PT groups possessed their own unique core microbiome. Treponema denticola was predominant in PI with probing depth of 8-10 mm. Interestingly, Thermovirga lienii DSM 17291 and Dialister invisus DSM 15470 were found to associate with PI. Nonsurgical treatment for peri-implantitis did not significantly alter the microbiome, except Rothia aeria.

CONCLUSION

Our study suggests Treponemas species may play a pivotal role in peri-implantitis. Nonsurgical treatment did not exert a major influence on the peri-implantitis microbiome in short-term follow-up. PT and peri-implantitis possess the unique microbiome profiles, and different therapeutic strategies may be suggested in the future.

Biomaterials science and surface engineering strategies for dental peri-implantitis management

Peri-implantitis is a bacterial infection that causes soft tissue inflammatory lesions and alveolar bone resorption, ultimately resulting in implant failure. Dental implants for clinical use barely have antibacterial properties, and bacterial colonization and biofilm formation on the dental implants are major causes of peri-implantitis. Treatment strategies such as mechanical debridement and antibiotic therapy have been used to remove dental plaque. However, it is particularly important to prevent the occurrence of peri-implantitis rather than treatment. Therefore, the current research spot has focused on improving the antibacterial properties of dental implants, such as the construction of specific micro-nano surface texture, the introduction of diverse functional coatings, or the application of materials with intrinsic antibacterial properties. The aforementioned antibacterial surfaces can be incorporated with bioactive molecules, metallic nanoparticles, or other functional components to further enhance the osteogenic properties and accelerate the healing process. In this review, we summarize the recent developments in biomaterial science and the modification strategies applied to dental implants to inhibit biofilm formation and facilitate bone-implant integration. Furthermore, we summarized the obstacles existing in the process of laboratory research to reach the clinic products, and propose corresponding directions for future developments and research perspectives, so that to provide insights into the rational design and construction of dental implants with the aim to balance antibacterial efficacy, biological safety, and osteogenic property.

Do Concurrent Peri-Implantitis and Periodontitis Share Their Microbiotas? A Pilot Study

The microbial compositions from concurrent peri-implant and periodontal lesions were compared, since the results reported in the literature on the etiological relationship between these oral pathologies are contradictory. Microbial compositions from nine patients were evaluated using Illumina MiSeq sequencing of 16S rRNA gene amplicons and Principal Components Analysis. Comparisons between the use of curettes or paper points as collection methods and between bacterial composition in both pathologies were performed. Paper points allowed the recovery of a higher number of bacterial genera. A higher bacterial diversity was found in peri-implantitis compared to periodontal samples from the same patient, while a greater number of operational taxonomic units (OTUs) were present in the corresponding periodontal samples. A higher abundance of oral pathogens, such as Porphyromonas or Treponema, was found in peri-implantitis sites. The opposite trend was observed for Aggregatibacter abundance, which was higher in periodontal than in peri-implantitis lesions, suggesting that both oral pathologies could be considered different but related diseases. Although the analysis of a higher number of samples would be needed, the differences regarding the microbial composition provide a basis for further understating the pathogenesis of peri-implant infections.

Microbiological profile of peri-implantitis: Analyses of peri-implant microbiome

PURPOSE

To characterize the microbiome composition in peri-implant pocket of peri-implantitis and peri-implant sulcus controls using 16S rRNA gene sequencing.

MATERIALS AND METHODS

In this controlled clinical cross-sectional study, 23 subjects with control implants (n = 14) and diseased implants (peri-implantitis, n = 21) were included. The peri-implant pocket/sulcus was sampled and used to extract DNA and amplify the 16S rRNA gene using universal primers targeting the V3-V4 regions. The resulting 16S PCR amplicons were sequenced on Illumina MiSeq, and the sequences were processed using DADA2 and the Human Oral Microbiome Database (HOMD) as references. Alpha and Beta diversity, as well as core microbiome and differential abundance analyses, were performed using the MicrobiomeAnalyst workflow.

RESULTS

There were no significant differences in microbial diversity between control implants and implants with peri-implantitis (Shannon p = 0.82). Overall bacterial community structure assessed through beta diversity analysis was also not significantly different between the two groups (p = 0.18). However, high levels of Gram-negative bacteria were detected in peri-implant pockets compared to the control sulcus. Abundant species in peri-implantitis were Capnocytophaga leadbetteri, Treponema maltophilum, Peptostreptococcus, Neisseria, P. gingivalis, and Porphyromonas endodontali, Lactococcus lactis and Filifactor alocis (p < 0.05). Gram-positive bacteria such as Streptococcus salivaris, Prevotella melaninogenica, L. wadei, and Actinomyces spp. serve were more abundant in peri-implant control sulcus.

CONCLUSIONS

Peri-implant sulcus in control implants harbors predominantly Gram-positive bacteria, whereas pockets of implants with peri-implantitis harbor predominantly Gram-negative bacteria.

The Peri-Implant Microbiome-A Possible Factor Determining the Success of Surgical Peri-Implantitis Treatment?

The objective was to assess the effect of peri-implantitis surgery on the peri-implant microbiome with a follow-up of one year. A total of 25 peri-implantitis patients in whom non-surgical treatment has failed to solve peri-implantitis underwent resective surgical treatment. Their peri-implant pockets were sampled prior to surgical treatment (T0) and one year post treatment (T12). The natural dentition was sampled to analyse similarities and differences with the peri-implantitis samples. Treatment success was recorded. The change in microbial relative abundance levels was evaluated. The microbiota was analysed by sequencing the amplified V3-V4 region of the 16S rRNA genes. Sequence data were binned to amplicon sequence variants that were assigned to bacterial genera. Group differences were analysed using principal coordinate analysis, Wilcoxon signed rank tests, and t-tests. Beta diversity analyses reported a significant separation between peri-implantitis and natural dentition samples on T0 and T12, along with significant separations between successfully and non-successfully treated patients. Eubacterium was significantly lower on T12 compared to T0 for the peri-implantitis samples. Treponema and Eubacterium abundance levels were significantly lower in patients with treatment success on T0 and T12 versus no treatment success. Therefore, lower baseline levels of Treponema and Eubacterium seem to be associated with treatment success of peri-implantitis surgery. This study might aid clinicians in determining which peri-implantitis cases might be suitable for treatment and give a prognosis with regard to treatment success.

Metagenomic analysis of healthy and diseased peri-implant microbiome under different periodontal conditions: a cross-sectional study

BACKGROUND

Peri-implantitis is a polybacterial infection that can lead to the failure of dental implant rehabilitation. This study aimed to profile the microbiome of the peri-implant plaque and estimate the effect of periodontitis on it among 40 Chinese participants with dental implant prostheses and presenting with varying peri-implant and periodontal health states.

METHODS

Submucosal plaque samples were collected from four distinct clinical categories based on both their implant and periodontal health status at sampling point. Clinical examinations of dental implant and remaining teeth were carried out. Metagenomic analysis was then performed.

RESULTS

The microbiome of the peri-implantitis sites differed from that of healthy implant sites, both taxonomically and functionally. Moreover, the predominant species in peri-implantitis sites were slightly affected by the presence of periodontitis. T. forsythia, P. gingivalis, T. denticola, and P. endodontalis were consistently associated with peri-implantitis and inflammatory clinical parameters regardless of the presence of periodontitis. Prevotella spp. and P. endodontalis showed significant differences in the peri-implantitis cohorts under different periodontal conditions. The most distinguishing function between diseased and healthy implants is related to flagellar assembly, which plays an important role in epithelial cell invasion.

CONCLUSIONS

The composition of the peri-implant microbiome varied in the diseased and healthy states of implants and is affected by individual periodontal conditions. Based on their correlations with clinical parameters, certain species are associated with disease and healthy implants. Flagellar assembly may play a vital role in the process of peri-implantitis.

Microbiological profile of peri-implantitis: Analyses of microbiome within dental implants

PURPOSE

To characterize the microbiome composition within dental implants of peri-implantitis subjects and healthy controls using 16S rRNA gene sequencing.

MATERIALS AND METHODS

Twenty-three subjects with healthy (n = 11 implants) and diseased (peri-implantitis, n = 21) implants were included in this controlled clinical cross-sectional study. Samples were obtained from internal surfaces of dental implants using sterile paper points for microbiological analysis. DNA was extracted, and the16S rRNA gene was amplified using universal primers targeting the V3-V4 regions. The resulting 16S polymerize chain reaction amplicons were sequenced on Illumina MiSeq, and the sequences were processed using DADA2 and the Human Oral Microbiome Database (HOMD) as references. Alpha and Beta diversity, as well as core microbiome and differential abundance analyses were then performed using the MicrobiomeAnalyst workflow.

RESULTS

A significant increase in microbial diversity was observed in the internal implant surface of healthy implants compared with the internal surfaces of peri-implantitis (Shannon p = 0.02). Bacterial community structure was significantly different among groups (p = 0.012). High levels of Gram-positive bacteria were detected inside implants with peri-implantitis compared to healthy implants, especially Enterococci.

CONCLUSIONS

There is a shift in bacterial diversity inside implants with peri-implantitis from the healthy control. The microbial colonization within that space might contribute to the etiology of peri-implant disease.

The Microbiome of Peri-Implantitis: A Systematic Review of Next-Generation Sequencing Studies

(1) Introduction: Current evidence shows that mechanical debridement augmented with systemic and topical antibiotics may be beneficial for the treatment of peri-implantitis. The microbial profile of peri-implantitis plays a key role in identifying the most suitable antibiotics to be used for the treatment and prevention of peri-implantitis. This systematic review aimed to summarize and critically analyze the methodology and findings of studies which have utilized sequencing techniques to elucidate the microbial profiles of peri-implantitis. (2) Results: Fusobacterium, Treponema, and Porphyromonas sp. are associated with peri-implantitis. Veillonella sp. are associated with healthy implant sites and exhibit a reduced prevalence in deeper pockets and with greater severity of disease progression. Streptococcus sp. have been identified both in diseased and healthy sites. Neisseria sp. have been associated with healthy implants and negatively correlate with the probing depth. Methanogens and AAGPRs were also detected in peri-implantitis sites. (3) Methods: The study was registered with the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42023459266). The PRISMA criteria were used to select articles retrieved from a systematic search of the Scopus, Cochrane, and Medline databases until 1 August 2023. Title and abstract screening was followed by a full-text review of the included articles. Thirty-two articles were included in the final qualitative analysis. (4) Conclusions: A distinct microbial profile could not be identified from studies employing sequencing techniques to identify the microbiome. Further studies are needed with more standardization to allow a comparison of findings. A universal clinical parameter for the diagnosis of peri-implantitis should be implemented in all future studies to minimize confounding factors. The subject pool should also be more diverse and larger to compensate for individual differences, and perhaps a distinct microbial profile can be seen with a larger sample size.

Colonization dynamics of subgingival microbiota in recently installed dental implants compared to healthy teeth in the same individual: a 6-month prospective observational study

OBJECTIVES

To evaluate the colonization dynamics of subgingival microbiota established over six months around newly installed dental implants in periodontally healthy individuals, compared with their corresponding teeth.

METHODOLOGY

Seventeen healthy individuals assigned to receive single dental implants participated in the study. Subgingival biofilm was sampled from all implant sites and contralateral/ antagonist teeth on days 7, 30, 90, and 180 after implant installation. Microbiological analysis was performed using the Checkerboard DNA-DNA hybridization technique for detection of classical oral taxa and non-oral microorganisms. Significant differences were estimated by Mann-Whitney and Friedman tests, while associations between implants/teeth and target species levels were assessed by linear regression analysis (LRA). Significance level was set at 5%.

RESULTS

Levels of some species were significantly higher in teeth compared to implants, respectively, at day 7 ( V.parvula , 6 × 10 5 vs 3 × 105 ; Milleri streptococci , 2 × 10 6 vs 6 × 10 5 ; Capnocytophaga spp., 2 × 10 6 vs 9 × 10 5 ; E.corrodens , 2 × 10 6 vs 5 × 10 5 ; N. mucosa , 2 × 10 6 vs 5 × 10 5 ; S.noxia , 2 × 10 6 vs 3 × 10 5 ; T.socranskii , 2 × 10 6 vs 5 × 10 5 ; H.alvei , 4 × 10 5 vs 2 × 10 5 ; and Neisseria spp., 6 × 10 5 vs 4 × 10 4 ), day 30 ( V.parvula , 5 × 10 5 vs 10 5 ; Capnocytophaga spp., 1.3 × 10 6 vs 6.8 × 10 4 ; F.periodonticum , 2 × 10 6 vs 10 6 ; S.noxia , 6 × 10 5 vs 2 × 10 5 ; H.alvei , 8 × 10 5 vs 9 × 10 4 ; and Neisseria spp., 2 × 10 5 vs 10 6 ), day 120 ( V.parvula , 8 × 10 5 vs 3 × 10 5 ; S.noxia , 2 × 10 6 vs 0; and T.socranskii , 3 × 10 5 vs 8 × 10 4 ), and day 180 ( S.enterica subsp. enterica serovar Typhi, 8 × 10 6 vs 2 × 10 6 ) (p<0.05). Implants showed significant increases over time in the levels of F.nucleatum , Gemella spp., H.pylori , P.micra , S.aureus , S.liquefaciens , and T.forsythia (p<0.05). LRA found that dental implants were negatively correlated with high levels of S. noxia and V. parvula (β=-0.5 to -0.3; p<0.05).

CONCLUSIONS

Early submucosal microbiota is diverse and only a few species differ between teeth and implants in the same individual. Only 7 days after implant installation, a rich microbiota can be found in the peri-implant site. After six months of evaluation, teeth and implants show similar prevalence and levels of the target species, including known and new periodontopathic species.

Changes in bone graft height and influencing factors after sinus floor augmentation by using the lateral window approach: A clinical retrospective study of 1 to 2 years

STATEMENT OF PROBLEM

Recent systematic reviews have reported resorption of bone grafts after augmentation, but the influencing factors are numerous and uncertain. Different brands of bone graft and other factors may affect the bone formation effect after sinus floor augmentation.

PURPOSE

The purpose of this retrospective clinical study was to evaluate the graft material height changes after sinus floor augmentation with cone beam computed tomography (CBCT) and to investigate the potential influencing factors related to graft resorption.

MATERIAL AND METHODS

Four midsagittal cut CBCT images of 157 posterior maxillary implants after maxillary sinus floor elevation by using the lateral window approach with bone grafts from 116 patients were obtained. Four CBCT scans had been performed immediately (T0), 6 months (T1) and 12 months after bone grafting (T2), and 1.5 to 2 years after treatment (T3), and the distance between the implant platform and the grafted mucosa of the maxillary sinus floor was measured at 3 locations. Correlation coefficients of these parameters were calculated. A linear mixed model was used to investigate potential factors influencing graft height reduction, including the patient's sex, age, smoking status, periodontal status, graft brand, implant site, implant level, placement time, and residual bone height.

RESULTS

Mean ±standard deviation graft height at the mesial side of the implant (MeGH) was significantly decreased by 0.32 ±0.88 mm in the first 6 months, was gradually reduced after 6 months (0.26 ±0.43 mm), and then 1 to 2 years later increased to 0.39 ±0.97 mm. The changes in graft height at the center of the implant (CeGH) and graft height at the distal side (DiGH) groups were similar to those in the MeGH group. A significantly positive correlation was found among the height alterations in 3 locations (rs=0.954, P<.001). The linear mixed model showed that smoking was more likely to cause graft height reduction in MeGH (P=.034).

CONCLUSIONS

Graft height significantly decreased after maxillary sinus augmentation over 1 to 2 years. Smoking had a negative effect on graft height changes, while the 2 brands of graft and other factors had no significant effect.

Correlations between Dental Implant Infectious Pathologies and Maxillary Sinusitis: A Review Article

(1) Background: The demands of patients for aesthetic and functional rehabilitation of edentulous areas led to the use of dental implants as therapeutic means on an increasingly large scale. This aspect determined the appearance of some infectious pathologies with a peri-implant starting point that can be complicated by various sinus diseases. The purpose of this review article is to synthesize the existing information in the specialized literature regarding the existing correlations between peri-implant and maxillary sinusitis. (2) Methods: The articles published in five databases were researched using different combinations of search terms. We selected 12 articles from the 250 found, by applying the inclusion and exclusion criteria and removing duplicates. (3) Results: We analyzed the included studies and we found that all of them reported a positive correlation between maxillary sinusitis and peri-implant infectious diseases. There are also reported other pathologies with a peri-implant infectious disease as a starting point such as abscesses, oro-antral communications, or foreign body reactions due to implant or bone graft materials migration. (4) Conclusions: This scoping review highlighted the existence of correlations between peri-implant and sinus pathology and the importance of preventing peri-implant diseases of an infectious nature to avoid the occurrence of these complications.

Fit and forget: The future of dental implant therapy via nanotechnology

Unlike orthopedic implants, dental implants require the orchestration of both osseointegration at the bone-implant interface and soft-tissue integration at the transmucosal region in a complex oral micro-environment with ubiquitous pathogenic bacteria. This represents a very challenging environment for early acceptance and long-term survival of dental implants, especially in compromised patient conditions, including aged, smoking and diabetic patients. Enabling advanced local therapy from the surface of titanium-based dental implants via novel nano-engineering strategies is emerging. This includes anodized nano-engineered implants eluting growth factors, antibiotics, therapeutic nanoparticles and biopolymers to achieve maximum localized therapeutic action. An important criterion is balancing bioactivity enhancement and therapy (like bactericidal efficacy) without causing cytotoxicity. Critical research gaps still need to be addressed to enable the clinical translation of these therapeutic dental implants. This review informs the latest developments, challenges and future directions in this domain to enable the successful fabrication of clinically-translatable therapeutic dental implants that would allow for long-term success, even in compromised patient conditions.

Clinical and Radiological Characterization of the Long-Term Association between Unaffected/Minimally Affected Implants and History of Severe Periodontitis: A Retrospective Study

OBJECTIVES

The objectives of this research were to compare, retrospectively, the clinical and radiographic modifications of periodontal parameters and peri-implant conditions and to analyze the relationship between the changes in periodontal parameters and peri-implant conditions over a mean follow-up period of 7.6 years in a treated population with progressive/uncontrolled periodontitis and at least one unaffected/minimally affected implant.

MATERIALS AND METHODS

Nineteen partially edentulous patients having 77 implants inserted, with a mean age of 54.84 ± 7.60 years, were matched for age, gender, compliance, smoking status, general health, and implant characteristics. Periodontal parameters were evaluated in the remaining teeth. Means per teeth and implants were used when making comparisons.

RESULTS

Statistically significant differences were observed between baseline and final examination in teeth for tPPD, tCAL and MBL. Furthermore, at 7.6 years, statistically significant differences existed between implants and teeth with regard to iCAL and tCAL (p = 0.03). Multiple regression analyses were performed and revealed a significant association regarding iPPD and CBL with smoking and periodontal diagnosis. In addition, FMBS was significantly associated with CBL. Unaffected/minimally affected implants were found more frequently in the posterior mandible, with longer lengths (>10 mm) and small diameters (<4 mm), including in screwed multi-unit bridges.

CONCLUSIONS

The study results appear to reflect minimally affected mean crestal bone-level loss around implants in comparison to the marginal bone-level loss around teeth when exposed to uncontrolled severe periodontal disease over a mean period of observation of 7.6 years, while the unaffected/minimally affected implants seemed to benefit from a combination of clinical factors, including posterior mandibular position, smaller diameters, and screwed multi-unit restorations.

The effect of motivational interviewing based on the transtheoretical model on oral cleaning behavior of patients with periodontitis who have undergone implant restoration

BACKGROUND

Implant-restored patients with periodontitis have a higher risk of developing peri-implantitis, and helping them develop oral cleaning habits is significant.

OBJECTIVE

To evaluate the effectiveness of motivational interviewing based on the transtheoretical model on the modification of oral cleaning behaviors of implant-restored patients with periodontitis.

METHODS

Patients with periodontitis (n= 70) who would receive dental implant treatment were included. And they were randomly divided into two groups: experimental (n= 35) and control (n= 35). Control patients received routine oral hygiene education, and those in the experimental group received motivational interviewing based on the transtheoretical model. Oral cleaning behavior was compared between the two groups before and after intervention. In addition, periodontal health status was compared on the day of implant restoration and three months later.

RESULTS

Compared to the control, the experimental group demonstrated significantly better oral hygiene behavior after intervention (P< 0.05). Three months after implant restoration, significantly better results were obtained by the experimental group in terms of mPLI and mSBI (P< 0.05).

CONCLUSION

Motivational interviewing based on the transtheoretical model can effectively improve the oral cleaning behavior and periodontal health of implant-restored patients with periodontitis.

Construction of a caries diagnosis model based on microbiome novelty score

OBJECTIVES

This study aimed to analyze the bacteria in dental caries and establish an optimized dental-ca-ries diagnosis model based on 16S ribosomal RNA (rRNA) data of oral flora.

METHODS

We searched the public databa-ses of microbiomes including NCBI, MG-RAST, EMBL-EBI, and QIITA and collected data involved in the relevant research on human oral microbiomes worldwide. The samples in the caries dataset (1 703) were compared with healthy ones (20 540) by using the microbial search engine (MSE) to obtain the microbiome novelty score (MNS) and construct a caries diagnosis model based on this index. Nonparametric multivariate ANOVA was used to analyze and compare the impact of different host factors on the oral flora MNS, and the model was optimized by controlling related factors. Finally, the effect of the model was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

1) The oral microbiota distribution obviously differed among people with various oral-health statuses, and the species richness and species diversity index decreased. 2) ROC curve was used to evaluate the caries data set, and the area under ROC curve was AUC=0.67. 3) Among the five hosts' factors including caries status, country, age, decayed missing filled tooth (DMFT) indices, and sampling site displayed the strongest effect on MNS of samples (P=0.001). 4) The AUC of the model was 0.87, 0.74, 0.74, and 0.75 in high caries, medium caries, low caries samples in Chinese children, and mixed dental plaque samples after controlling host factors, respectively.

CONCLUSIONS

The model based on the analysis of 16S rRNA data of oral flora had good diagnostic efficiency.

In silico evaluation and selection of the best 16S rRNA gene primers for use in next-generation sequencing to detect oral bacteria and archaea

BACKGROUND

Sequencing has been widely used to study the composition of the oral microbiome present in various health conditions. The extent of the coverage of the 16S rRNA gene primers employed for this purpose has not, however, been evaluated in silico using oral-specific databases. This paper analyses these primers using two databases containing 16S rRNA sequences from bacteria and archaea found in the human mouth and describes some of the best primers for each domain.

RESULTS

A total of 369 distinct individual primers were identified from sequencing studies of the oral microbiome and other ecosystems. These were evaluated against a database reported in the literature of 16S rRNA sequences obtained from oral bacteria, which was modified by our group, and a self-created oral archaea database. Both databases contained the genomic variants detected for each included species. Primers were evaluated at the variant and species levels, and those with a species coverage (SC) ≥75.00% were selected for the pair analyses. All possible combinations of the forward and reverse primers were identified, with the resulting 4638 primer pairs also evaluated using the two databases. The best bacteria-specific pairs targeted the 3-4, 4-7, and 3-7 16S rRNA gene regions, with SC levels of 98.83-97.14%; meanwhile, the optimum archaea-specific primer pairs amplified regions 5-6, 3-6, and 3-6, with SC estimates of 95.88%. Finally, the best pairs for detecting both domains targeted regions 4-5, 3-5, and 5-9, and produced SC values of 95.71-94.54% and 99.48-96.91% for bacteria and archaea, respectively.

CONCLUSIONS

Given the three amplicon length categories (100-300, 301-600, and >600 base pairs), the primer pairs with the best coverage values for detecting oral bacteria were as follows: KP_F048-OP_R043 (region 3-4; primer pair position for Escherichia coli J01859.1: 342-529), KP_F051-OP_R030 (4-7; 514-1079), and KP_F048-OP_R030 (3-7; 342-1079). For detecting oral archaea, these were as follows: OP_F066-KP_R013 (5-6; 784-undefined), KP_F020-KP_R013 (3-6; 518-undefined), and OP_F114-KP_R013 (3-6; 340-undefined). Lastly, for detecting both domains jointly they were KP_F020-KP_R032 (4-5; 518-801), OP_F114-KP_R031 (3-5; 340-801), and OP_F066-OP_R121 (5-9; 784-1405). The primer pairs with the best coverage identified herein are not among those described most widely in the oral microbiome literature. Video Abstract.

Reduced proinflammatory activity of outer membrane vesicles of Tannerella forsythia treated with quorum sensing inhibitors

Outer membrane vesicles (OMVs) of bacteria harbor physiologically active molecules, and quorum sensing inhibitors (QSIs) are expected to regulate bacterial virulence. In this study, we analyzed the proinflammatory activity of OMVs of the periodontal pathogen Tannerella forsythia treated with d-arabinose and d-galactose as QSIs, which inhibit the biofilm formation of periodontal pathogens and autoinducer 2 activity. Compared to OMVs of nontreated T. forsythia (TF OMVs), OMVs released from QSI-treated T. forsythia, designated TF ara-OMVs and TF gal-OMVs, showed reduced production of TNF-α, IL-1β, IL-6, and IL-8 in THP-1 monocytes through decreased activation of NF-κB/MAPKs. Using a human NF-κB reporter cell line and bone marrow-derived macrophages from TLR2^-/- mice, TF ara-OMVs and TF gal-OMVs showed less activation of TLR2 than TF OMVs. These results demonstrated that QSIs provide a dual advantage against bacterial infection by inhibiting bacterial biofilm formation and generating OMVs with reduced proinflammatory activity.

Extracts of Rheum palmatum and Aloe vera Show Beneficial Properties for the Synergistic Improvement of Oral Wound Healing

Various local and systemic factors compromise oral wound healing and may lead to wound dehiscence, inflammation, or ulcers. Currently, there is a lack of topical therapeutical options. Thus, this study aimed to investigate the effect of Aloe vera (AV) and Rheum palmatum root (RPR) on oral wound healing capacity in vitro. The effect of AV and RPR on human primary fibroblast viability and migration was studied by measuring metabolic activity and gap closure in a scratch assay. Furthermore, cell cycle distribution and cytoskeletal features were analyzed. Antimicrobial activity against the oral pathogen Porphyromonas gingivalis was evaluated by broth microdilution assay. AV and RPR increased fibroblast migration after single agent treatment. Synergistic effects of the plant extract combination were observed regarding cellular migration which were confirmed by calculation of the phenomenological combination index (pCI), whereas the cell cycle distribution was not influenced. Furthermore, the combination of AV and RPR showed synergistic antibacterial effects as determined by the fractional inhibitory concentration index. This study demonstrated that the combination of AV and RPR can promote the migration of human primary fibroblasts in vitro and exert antimicrobial efficacy against P. gingivalis, suggesting these compounds for the topical treatment of wound healing disorders.

Microbial profiling of peri-implantitis compared to the periodontal microbiota in health and disease using 16S rRNA sequencing

PURPOSE

The objective of this study was to analyze the microbial profile of individuals with peri-implantitis (PI) compared to those of periodontally healthy (PH) subjects and periodontitis (PT) subjects using Illumina sequencing.

METHODS

Buccal, supragingival, and subgingival plaque samples were collected from 109 subjects (PH: 30, PT: 49, and PI: 30). The V3-V4 region of 16S rRNA was sequenced and analyzed to profile the plaque microbiota.

RESULTS

Microbial community diversity in the PI group was higher than in the other groups, and the 3 groups showed significantly separated clusters in the buccal samples. The PI group showed different patterns of relative abundance from those in the PH and PT groups depending on the sampling site at both genus and phylum levels. In all samples, some bacterial species presented considerably higher relative abundances in the PI group than in the PH and PT groups, including Anaerotignum lactatifermentans, Bacteroides vulgatus, Faecalibacterium prausnitzii, Olsenella uli, Parasutterella excrementihominis, Prevotella buccae, Pseudoramibacter alactolyticus, Treponema parvum, and Slackia exigua. Network analysis identified that several well-known periodontal pathogens and newly recognized bacteria were closely correlated with each other.

CONCLUSIONS

The composition of the microbiota was considerably different in PI subjects compared to PH and PT subjects, and these results could shed light on the mechanisms involved in the development of PI.

The Main Bacterial Communities Identified in the Sites Affected by Periimplantitis: A Systematic Review

(1) Background: Periimplantitis is an infectious condition that affects the periimplant tissue and is of bacterial etiology. However, to date, the exact bacterial flora involved in its occurrence is not known. The aim of this literature review was to summarize the articles published on this topic and to identify the main bacterial species isolated in periimplantitis. (2) Methods: The articles published in three databases were researched: Pubmed, Embase and Web of Science using Prisma guides and combinations of MeSH terms. We selected 25 items from the 980 found by applying the inclusion and exclusion criteria. (3) Results: We quantified the results of the 25 studies included in this review. In general, the most commonly identified bacterial species were Gram-negative anaerobic species, as Prevotella, Streptococcus, Fusobacterium and Treponema. (4) Conclusion: The most frequent bacteria in the periimplantitis sites identified in this review are Gram-negative anaerobic species, also involved in the pathogenesis of the periodontal disease.

Oral Microbiota, a Potential Determinant for the Treatment Efficacy of Gastric Helicobacter pylori Eradication in Humans

The oral cavity serves as another reservoir for gastric Helicobacter pylori and may contribute to the failure of gastric H. pylori eradication therapy. However, changes to the oral microbial composition after gastric H. pylori eradication therapy has not yet been identified. This study aims to dissect whether the oral microbiota is involved and which bacterium mediates the clinic failure in H. pylori eradication. In the present study, the oral microorganisms from patients who had received the gastric H. pylori eradication treatment were analyzed by a high-throughput 16S rRNA deep sequencing. We found that the β diversity and composition of oral microbiota were remarkably changed in the patients who had experienced successful gastric H. pylori eradication treatment (SE group) compared to the failure group (FE group). Significantly enriched families, including Prevotellaceae, Streptococcaceae, Caulobacteraceae, and Lactobacillaceae, were detected in the SE group. In contrast, the bacterial families, such as Weeksellaceae, Neisseriaceae, Peptostreptococcaceae, Spirochaetaceae, and Veillonellaceae, were abundantly expressed in the FE group. Five operational taxonomic units (OTUs) were positively correlated with DOB values, while two OTUs exhibited negative trends. These different enriched OTUs were extensively involved in the 20 metabolic pathways. These results suggest that a balanced environment in the oral microbiota contributes to H. pylori eradication and metabolic homeostasis in humans. Our data demonstrated that the changes in oral microbiota might contribute to the therapeutic effects of antibiotic therapy. Therefore, a different therapy on the detrimental oral microbiota will increase the therapeutic efficacy of antibiotics on H. pylori infection.

The Plaque Microbiota Community of Giant Panda (Ailuropoda melanoleuca) Cubs With Dental Caries

Dental caries severely hinders efficient access to adequate energy in wildlife. Different food supplies will develop characteristic plaque, and the microorganisms of these plaque are closely related to dental health. Here, plaque samples from panda cubs with caries and caries-free were collected for 16S rRNA high-throughput sequencing. All sequences clustered into 337 operational taxonomic units (OTUs; 97% identity), representing 268 independent species belonging to 189 genera, 98 families, 51 orders, 24 classes, and 13 phyla. Two groups shared 218 OTUs, indicating the presence of a core plaque microbiome. α diversity analysis showed that the microbial diversity in plaques with caries exceeded that of caries-free. The dominant phyla of plaque microbiota included Proteobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Actinobacteria. The dominant genera included unclassified Neisseriaceae, Actinobacillus, Lautropia, Neisseria, Porhyromonas, unclassified Pasteurellaceae, Moraxella, Streptococcus, Bergeywlla and Capnocytophaga. β diversity analysis showed that the plaque microbial community structure was different between two groups. Using LEfSe analysis, 19 differentially abundant taxa were identified as potential biomarkers. Finally, function predictions analysis showed All the energy related metabolic pathways on KEGG level 2 were enriched in caries-active group. Consistent with the mainstream caries-causing narrative, our results illuminate the lack of information regarding the oral microflora composition and function within giant panda cubs.

Microbiota in Gingival Crevicular Fluid Before and After Mechanical Debridement With Antimicrobial Photodynamic Therapy in Peri-Implantitis

Objectives

This study aims to compare the microbiota of gingival crevicular fluid (GCF) before and after mechanical debridement (MD) with antimicrobial photodynamic therapy (aPDT) and determine the core efficient microbiota in peri-implantitis after treatment.

Methods

We recruited 9 patients (14 implants) treated with MD+aPDT for peri-implantitis at our center from February 1, 2018, to February 1, 2019. GCF was collected using filter paper strip before and after the treatment. The bacterial 16S rRNA was amplified and sequenced using an Illumina MiSeq platform to characterize the GCF. Bioinformatics and statistical analyses were performed using QIIME2 and R.

Results

A total of 4,110,861 high-quality sequences were obtained from GCF samples. Based on the reference database, 1,120 amplicon sequence variants (ASVs) were finally harvested. Principal coordinates analysis indicated significant differences in the bacterial community structure between the 180 days after-treatment group and pre-treatment group. Difference analysis and least discriminant analysis showed that the differences were mainly reflected in non-dominant bacteria between these two groups. The non-dominant genera with significantly different distribution between the 180 days after-treatment group and the pre-treatment group included Lactobacillus, Pedobacter, Bulleidia, Centipeda, Desulfovibrio, Ochrobactrum, Staphylococcus, Microbacterium, Brevundimonas, Desulfobulbus, and Parvimonas. Moreover, a total of 29 predictive functional categories at KEGG level 2 were identified. The significant difference pathways at KEGG level 2 between after-treatment and pre-treatment were concentrated in infectious disease-related pathways.

Conclusions

Patients with peri-implantitis have significant changes in the low-abundance bacteria of the GCF before and after MD+aPDT. MD+aPDT may change the composition of GCF microbiota by increasing the abundance of cluster 1 (beneficial) and decreasing that of cluster 4 (harmful), which may decrease metabolic response to infection and thus improve peri-implantitis.

Oral Microbiota in Patients with Peri-Implant Disease: A Narrative Review

Peri-implant infections are the most common complications related to the placement of dental implants. There are many microbial similarities between peri-implantitis and periodontitis but due to current laboratory techniques there are just as many differences. This review was performed to assess changes in the oral microbiota at sites with peri-implant disease, according to the state of the art. The peri-implant microbiota presents a lower microbial quality than the periodontal microbiota, becoming increasingly complex as it progresses from peri-implant mucositis to peri-implantitis. The microbial difference detected between the peri-implant and periodontal microbiota is primarily related to whole bacterial populations, rather than specific bacterial taxa. The use of probiotics could support the reduction of peri-implant pockets, in association with mechanical debridement, due to their mechanism of action of competitive inhibition for adhesion sites. The peri-implant microbiota represents a qualitatively inferior but quantitatively superior bacterial ecosystem for some bacterial genera compared to the periodontal microbiota, showing that a progression from healthy state to peri-implantitis causes changes in microbiota composition in the absence of specific disease-causing bacteria. Transcriptomics could provide useful information for the prevention, diagnosis, and therapy of peri-implant pathology through knowledge of bacterial virulence factors.

Discrimination of Bacterial Community Structures among Healthy, Gingivitis, and Periodontitis Statuses through Integrated Metatranscriptomic and Network Analyses

Periodontal disease is an inflammatory condition caused by polymicrobial infection. The inflammation is initiated at the gingiva (gingivitis) and then extends to the alveolar bone, leading to tooth loss (periodontitis). Previous studies have shown differences in bacterial composition between periodontal healthy and diseased sites. However, bacterial metabolic activities during the health-to-periodontitis microbiome shift are still inadequately understood. This study was performed to investigate the bacterial characteristics of healthy, gingivitis, and periodontitis statuses through metatranscriptomic analysis. Subgingival plaque samples of healthy, gingivitis, and periodontitis sites in the same oral cavity were collected from 21 patients. Bacterial compositions were then determined based on 16S rRNA reads; taxonomic and functional profiles derived from genes based on mRNA reads were estimated. The results showed clear differences in bacterial compositions and functional profiles between healthy and periodontitis sites. Co-occurrence networks were constructed for each group by connecting two bacterial species if their mRNA abundances were positively correlated. The clustering coefficient values were 0.536 for healthy, 0.600 for gingivitis, and 0.371 for periodontitis sites; thus, network complexity increased during gingivitis development, whereas it decreased during progression to periodontitis. Taxa, including Eubacterium nodatum, Eubacterium saphenum, Filifactor alocis, and Fretibacterium fastidiosum, showed greater transcriptional activities than those of red complex bacteria, in conjunction with disease progression. These taxa were associated with periodontal disease progression, and the health-to-periodontitis microbiome shift was accompanied by alterations in bacterial network structure and complexity.

IMPORTANCE The characteristics of the periodontal microbiome influence clinical periodontal status. Gingivitis involves reversible gingival inflammation without alveolar bone resorption. In contrast, periodontitis is an irreversible disease characterized by inflammatory destruction in both soft and hard tissues. An imbalance of the microbiome is present in both gingivitis and periodontitis. However, differences in microbiomes and their functional activities in the healthy, gingivitis, and periodontitis statuses are still inadequately understood. Furthermore, some inflamed gingival statuses do not consistently cause attachment loss. In this study, metatranscriptomic analyses were used to investigate the specific bacterial composition and gene expression patterns of the microbiomes of the healthy, gingivitis, and periodontitis statuses. In addition, co-occurrence network analysis revealed that the gingivitis site included features of networks observed in both the healthy and periodontitis sites. These results provide transcriptomic evidence to support gingivitis as an intermediate state between the healthy and periodontitis statuses.

Microbial profiles of peri-implant mucositis and peri-implantitis: Submucosal microbial dysbiosis correlates with disease severity

OBJECTIVE

To investigate the microbiome characteristics of peri-implant mucositis (PM) and peri-implantitis (PI), and to analyse the correlation between disease severity and submucosal microbial dysbiosis.

MATERIALS AND METHODS

A cross-sectional study design was conducted. Submucosal biofilm samples from 27 PM sites and 37 PI sites from 64 patients were collected and analysed using 16S rRNA gene sequencing (Illumina). Differences in microbiological profiles between PM and PI were evaluated using the α-diversity, β-diversity and linear discriminant analysis effect size (LEfSe) analysis. The relative abundances of the taxa at the phylum and genus levels were compared using the Wilcoxon rank test and logistic regression. The microbial dysbiosis index (MDI) was calculated, and its relationship with clinical measurements (probing depth, bleeding on probing and marginal bone loss, among others) was analysed using Pearson's correlation coefficient.

RESULTS

The overall microbiome distribution in the PM and PI sites was similar according to α- and β-diversity. Twenty-three taxa at the genus level and two taxa at the phylum level showed significant differences in relative abundance between the two clinical classifications. Five taxa at the genus level were screened out for the MDI calculation after logistic regression. No clinical measurements but marginal bone loss showed a significant positive correlation with microbial dysbiosis.

CONCLUSION

The microbiome richness, diversity and distribution were similar in PM and PI sites, including both common periodontal bacteria and novel species. In addition, an increase in marginal bone loss was significantly associated with submucosal microbial dysbiosis.

Comparison of Periodontal Bacteria of Edo and Modern Periods Using Novel Diagnostic Approach for Periodontitis With Micro-CT

Ancient dental calculus, formed from dental plaque, is a rich source of ancient DNA and can provide information regarding the food and oral microbiology at that time. Genomic analysis of dental calculus from Neanderthals has revealed the difference in bacterial composition of oral microbiome between Neanderthals and modern humans. There are few reports investigating whether the pathogenic bacteria of periodontitis, a polymicrobial disease induced in response to the accumulation of dental plaque, were different between ancient and modern humans. This study aimed to compare the bacterial composition of the oral microbiome in ancient and modern human samples and to investigate whether lifestyle differences depending on the era have altered the bacterial composition of the oral microbiome and the causative bacteria of periodontitis. Additionally, we introduce a novel diagnostic approach for periodontitis in ancient skeletons using micro-computed tomography. Ancient 16S rDNA sequences were obtained from 12 samples at the Unko-in site (18th-19th century) of the Edo era (1603–1867), a characteristic period in Japan when immigrants were not accepted. Furthermore, modern 16S rDNA data from 53 samples were obtained from a database to compare the modern and ancient microbiome. The microbial co-occurrence network was analyzed based on 16S rDNA read abundance. Eubacterium species, Mollicutes species, and Treponema socranskii were the core species in the Edo co-occurrence network. The co-occurrence relationship between Actinomyces oricola and Eggerthella lenta appeared to have played a key role in causing periodontitis in the Edo era. However, Porphyromonas gingivalis, Fusobacterium nucleatum subsp. vincentii, and Prevotella pleuritidis were the core and highly abundant species in the co-occurrence network of modern samples. These results suggest the possibility of differences in the pathogens causing periodontitis during different eras in history.

Application of biomaterials in periodontal tissue repair and reconstruction in the presence of inflammation under periodontitis through the foreign body response: Recent progress and perspectives

Periodontitis would cause dental tissue damage locally. Biomaterials substantially affect the surrounding immune microenvironment through treatment-oriented local inflammatory remodeling in dental periodontitis. This remodeling process is conducive to wound healing and periodontal tissue regeneration. Recent progress in understanding the foreign body response (FBR) and immune regulation, including cell heterogeneity, and cell-cell and cell-material interactions, has provided new insights into the design criteria for biomaterials applied in treatment of periodontitis. This review discusses recent progress and perspectives in the immune regulation effects of biomaterials to augment or reconstruct soft and hard tissue in an inflammatory microenvironment of periodontitis.

Bioactive coatings for dental implants: A review of alternative strategies to prevent peri-implantitis induced by anaerobic bacteria

Members of oral bacterial communities form biofilms not only on tooth surfaces but also on the surface of dental implants that replace natural teeth. Prolonged interaction of host cells with biofilm-forming anaerobes frequently elicits peri-implantitis, a destructive inflammatory disease accompanied by alveolar bone loss leading to implant failure. Here we wish to overview how the deposition of bioactive peptides to dental implant surfaces could potentially inhibit bacterial colonization and the development of peri-implantisis. One preventive strategy is based on natural antimicrobial peptides (AMPs) immobilized on titanium surfaces. AMPs are capable to destroy both Gram positive and Gram negative bacteria directly. An alternative strategy aims at coating implant surfaces - especially the transmucosal part - with peptides facilitating the attachment of gingival epithelial cells and connective tissue cells. These cells produce AMPs and may form a soft tissue seal that prevents oral bacteria from accessing the apical part of the osseointegrated implant. Because a wide variety of titanium-bound peptides were studied in vitro, we wish to concentrate on bioactive peptides of human origin and some of their derivatives. Furthermore, special attention will be given to peptides effective under in vivo test conditions.

Novel application of bergapten and quercetin with anti-bacterial, osteogenesis-potentiating, and anti-inflammation tri-effects

The bacteria-mediated inflammatory conditions adversely affect the osseointegration process of endosseous implants, which can even lead to implant malfunction or failure. Local drug delivery has been designed to exert anti-inflammatory and antibacterial activities, but whether this strategy has an effect on the compromised osseointegration under inflammation has rarely been studied. The present study focused on the osteoinductive efficacy of two known phytoestrogens [bergapten (BP) and quercetin (QE)] on implant sites under multiple bacteria-infected conditions in situ. Furthermore, the gene expression profiles of rat bone mesenchymal stem cells (rBMSCs) treated with BP and QE in the presence of Porphyromonas gingivalis-derived lipopolysaccharide were identified. The results showed that both drugs, especially QE, had significant potentiating effects on promoting osteogenic differentiation of rBMSCs, resisting multiple pathogens, and reducing inflammatory activity. Meanwhile, RNA sequencing analysis highlighted the enriched gene ontology terms and the differentially expressed genes (Vps25, Il1r2, Csf3, Efemp1, and Ccl20) that might play essential roles in regulating the above tri-effects, which provided the basis for the drug delivery system to be used as a novel therapeutic strategy for integrating peri-implant health. Overall, our study confirmed that QE appeared to outperform BP in osteogenesis and bacterial killing but not in anti-inflammation. Moreover, both drugs possess favorable tri-effects and can serve as the pivotal agents for the drug delivery system to boost osseointegration at inflammatory implant sites.

The occurrence of peri-implant mucositis associated with the shift of submucosal microbiome in patients with a history of periodontitis during the first two years

AIM

To investigate the dynamic changes of peri-implant microbiome in patients with a history of periodontitis and to construct a microbial prediction model.

MATERIALS AND METHODS

The prospective study was performed at one month (T1), one year (T2) and two years (T3) after restoration. Clinical examinations [probing depth (PD), bleeding on probing (BOP), suppuration (SUP)], radiographic examinations and sample collection were conducted at three timepoints. Peri-implant sulcular fluid (PISF) was collected and analysed by 16S rRNA gene sequencing. Generalized linear mixed model (GLMM) was used to identify differences.

RESULTS

Totally, 168 subjects were assessed for eligibility. Twenty-two patients were recruited in the longitudinal study. Eventually, 67 PISF samples from 24 implants of 12 patients were collected and analysed. Peri-implant microbiome showed increasing diversity and complexity over time. Disease-associated genera Porphyromonas, Tannerella, Treponema and Prevotella dramatically increased from T1 to T3. The prediction model for clinical suppuration at T1 showed a high accuracy of 90%.

CONCLUSION

The dysbiosis of peri-implant microbiome increased with time during the two-year observation in patients with a history of periodontitis. Genera of Porphyromonas, Tannerella, Treponema and Prevotella were biomarkers of peri-implant mucositis. Microbiota at the early stage could predict subsequent microbial dysbiosis and clinical suppuration.

In vitro Interactions between Streptococcus intermedius and Streptococcus salivarius K12 on a Titanium Cylindrical Surface

Peri-implantitis is a steadily rising disease and is caused by oral bacterial pathogens able to form biofilm on implant surfaces and peri-implant tissues, making antibiotics treatment less effective. The use of commercial probiotics against oral pathogens could serve as an alternative to prevent biofilm formation. Streptococcus intermedius is one of the early colonizers of biofilm formation in dental implants. The aim of this study was to model the interaction between S. intermedius and Streptococcus salivarius strain K12, a probiotic bacterium producing bacteriocins. S. intermedius was co-cultured with S. salivarius K12 in an in vitro model simulating the biofilm formation in a dental implant composed by a titanium cylinder system. Biofilm formation rate was assessed by Real-Time PCR quantification of bacterial count and expression levels of luxS gene, used in response to cell density in the biofilm. Biofilm formation, bacteriocin production, luxS expression patterns were found to be already expressed within the first 12 h. More importantly, S. salivarius K12 was able to counter the biofilm formation in a titanium cylinder under the tested condition. In conclusion, our dental implant model may be useful for exploring probiotic-pathogen interaction to find an alternative to antibiotics for peri-implantitis treatment.

Discriminating Microbial Community Structure Between Peri-Implantitis and Periodontitis With Integrated Metagenomic, Metatranscriptomic, and Network Analysis

Peri-implantitis and periodontitis are both polymicrobial diseases induced by subgingival plaque accumulation, with some differing clinical features. Studies on the microbial and gene transcription activity of peri-implantitis microbiota are limited. This study aimed to verify the hypothesis that disease-specific microbial and gene transcription activity lead to disease-specific clinical features, using an integrated metagenomic, metatranscriptomic, and network analysis. Metagenomic data in peri-implantitis and periodontitis were obtained from the same 21 subjects and metatranscriptomic data from 12 subjects were obtained from a database. The microbial co-occurrence network based on metagenomic analysis had more diverse species taxa and correlations than the network based on the metatranscriptomic analysis. Solobacterium moorei and Prevotella denticola had high activity and were core species taxa specific to peri-implantitis in the co-occurrence network. Moreover, the activity of plasmin receptor/glyceraldehyde-3-phosphate dehydrogenase genes was higher in peri-implantitis. These activity differences may increase complexity in the peri-implantitis microbiome and distinguish clinical symptoms of the two diseases. These findings should help in exploring a novel biomarker that assist in the diagnosis and preventive treatment design of peri-implantitis.

Titanium Corrosion in Peri-Implantitis

Titanium (Ti) corrodes clinically in the presence of bacteria. We investigated this phenomenon as a function of Ti particles found in biopsied tissues around peri-implantitis sites and surface roughness of failed Ti implants. Tissue biopsies were surgically collected from peri-implantitis sites, processed, and embedded in resin. The resin-embedded samples were hand trimmed to the region of interest and semi-thick (500 nm) sections were collected onto coverslips. One section was toluidine blue post-stained as a reference. The remainder sections were left unstained for energy-dispersive X-ray spectroscopy (EDX) analysis. Processed samples were examined under scanning electron microscopy (SEM) and EDX. Corresponding failed implants were also removed and examined under SEM and EDX. Five out of eight biopsied samples demonstrated the presence of Ti particles in the soft tissue, suggesting the true rate among all failures was between 24.5% and 91.5% (the lower bound of a 95% confidence interval for the true rate of Ti presence). SEM analysis of failed implant bodies also indicated changes in surface morphology and appeared less detailed with decreased weight percent of Ti on the surface of the failed implants. In conclusion, Ti particles were noted in 5/8 biopsied samples. Surface morphologies were smoother in failed implants compared with the reference implant.

Probing periodontal microbial dark matter using metataxonomics and metagenomics

Our view of the periodontal microbial community has been shaped by a century or more of cultivation-based and microscopic investigations. While these studies firmly established the infection-mediated etiology of periodontal diseases, it was apparent from the very early days that periodontal microbiology suffered from what Staley and Konopka described as the "great plate count anomaly", in that these culturable bacteria were only a minor part of what was visible under the microscope. For nearly a century, much effort has been devoted to finding the right tools to investigate this uncultivated majority, also known as "microbial dark matter". The discovery that DNA was an effective tool to "see" microbial dark matter was a significant breakthrough in environmental microbiology, and oral microbiologists were among the earliest to capitalize on these advances. By identifying the order in which nucleotides are arranged in a stretch of DNA (DNA sequencing) and creating a repository of these sequences, sequence databases were created. Computational tools that used probability-driven analysis of these sequences enabled the discovery of new and unsuspected species and ascribed novel functions to these species. This review will trace the development of DNA sequencing as a quantitative, open-ended, comprehensive approach to characterize microbial communities in their native environments, and explore how this technology has shifted traditional dogmas on how the oral microbiome promotes health and its role in disease causation and perpetuation.

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.

Strong oral plaque microbiome signatures for dental implant diseases identified by strain-resolution metagenomics

Dental implants are installed in an increasing number of patients. Mucositis and peri-implantitis are common microbial-biofilm-associated diseases affecting the tissues that surround the dental implant and are a major medical and socioeconomic burden. By metagenomic sequencing of the plaque microbiome in different peri-implant health and disease conditions (113 samples from 72 individuals), we found microbial signatures for peri-implantitis and mucositis and defined the peri-implantitis-related complex (PiRC) composed by the 7 most discriminative bacteria. The peri-implantitis microbiome is site specific as contralateral healthy sites resembled more the microbiome of healthy implants, while mucositis was specifically enriched for Fusobacterium nucleatum acting as a keystone colonizer. Microbiome-based machine learning showed high diagnostic and prognostic power for peri-implant diseases and strain-level profiling identified a previously uncharacterized subspecies of F. nucleatum to be particularly associated with disease. Altogether, we associated the plaque microbiome with peri-implant diseases and identified microbial signatures of disease severity.

Decontamination of rough implant surfaces colonized by multispecies oral biofilm by application of leukocyte- and platelet-rich fibrin

BACKGROUND

Decontamination of biofilm-infected rough implant surfaces is challenging. Platelet rich blood products have been shown to have anti-microbial properties against periodontal pathogens. Our aim was to investigate the effect of a potential biological implant surface disinfectant, leukocyte- and platelet-rich fibrin (L-PRF), on a mature oral multispecies biofilm on a rough titanium surface.

METHODS

Sandblasted, large grit, acid-etched (SLA) titanium disks were inoculated with subgingival dental plaque and cultured anaerobically for 21 days. The L-PRF membranes were collected from 12 donors in three trials (four donors in each trial). The disks were rinsed with 0.9% NaCl and exposed to the cell-rich portion of the L-PRF membranes for 48 hours followed by scanning electron microscope (SEM) analysis immediately or after rinsing with 0.9% NaCl prior to fixation. The presence of platelet factor-4 in the rinse samples was analyzed by Western blotting. Remaining bacteria were quantified from SEM images of the implant surfaces and their numbers statistically compared.

RESULTS

The L-PRF-treated samples without rinsing displayed numerous cells with multiple pseudopodia in immediate contact with bacteria that appeared perforated and increased in size. The cells were identified as platelets based on morphological criteria and by positive reaction for platelet factor-4 by Western blotting. After post-treatment rinsing, the L-PRF-treated disks displayed a significant reduction in bacterial counts (in average 92% reduction).

CONCLUSION

Application of L-PRF significantly reduced bacterial counts on contaminated SLA titanium surface, most likely through anti-microbial action by platelets.

Analysis of the Subgingival Microbiota in Implant-Supported Full-Arch Rehabilitations

Background: The etiology of peri-implantitis is multifactorial, and it is not directly linked to the quantitative amount of plaque. The aim of this study was to evaluate the influence of subgingival microbiota around implants supporting full-arch restorations on clinical indexes of peri-implant health. Method: 47 patients (54 full-arch fixed rehabilitations) were included. Based on the highest value of probing depth (PD), 47 implants (in the test arch), 40 natural teeth and 7 implants (in the antagonist arch) were selected for microbiological sampling (traditional PCR and real-time PCR). Periodontal indexes (plaque index, PlI; probing depth, PD; bleeding on probing, BOP; peri-implant suppuration, PS) and marginal bone loss were also recorded. Results: Despite abundant plaque accumulation, the peri-implant parameters were within normal limits. No statistical difference was found in the microbial population around the test implants and antagonist natural teeth. Treponema denticola was present in a significantly higher amount around implants with increased PlI. Implants with increased BOP showed a significant increase in Treponema denticola and Tannerella forsythia. A significantly higher presence of Porphyromonas gingivalis, Treponema denticola and Tannerella forsythia was identified around the implants affected by peri-implantitis and in smokers. Conclusions: Peri-implantitis is characterized by a complex and polymicrobial disease, that might be influenced by the qualitative profile of plaque. Smoking might also favor implant biological complications in full-arch fixed prosthesis.

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

BACKGROUND

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).

METHODS

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 ≥4 mm 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.

RESULTS

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.

CONCLUSIONS

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.

Microbial Community-Driven Etiopathogenesis of Peri-Implantitis

Osseointegrated dental implants are a revolutionary tool in the armament of reconstructive dentistry, employed to replace missing teeth and restore masticatory, occlusal, and esthetic functions. Like natural teeth, the orally exposed part of dental implants offers a pristine nonshedding surface for salivary pellicle-mediated microbial adhesion and biofilm formation. In early colonization stages, these bacterial communities closely resemble those of healthy periodontal sites, with lower diversity. Because the peri-implant tissues are more susceptible to endogenous oral infections, understanding of the ecological triggers that underpin the microbial pathogenesis of peri-implantitis is central to developing improved prevention, diagnosis, and therapeutic strategies. The advent of next-generation sequencing (NGS) technologies, notably applied to 16S ribosomal RNA gene amplicons, has enabled the comprehensive taxonomic characterization of peri-implant bacterial communities in health and disease, revealing a differentially abundant microbiota between these 2 states, or with periodontitis. With that, the peri-implant niche is highlighted as a distinct ecosystem that shapes its individual resident microbial community. Shifts from health to disease include an increase in diversity and a gradual depletion of commensals, along with an enrichment of classical and emerging periodontal pathogens. Metatranscriptomic profiling revealed similarities in the virulence characteristics of microbial communities from peri-implantitis and periodontitis, nonetheless with some distinctive pathways and interbacterial networks. Deeper functional assessment of the physiology and virulence of the well-characterized microbial communities of the peri-implant niche will elucidate further the etiopathogenic mechanisms and drivers of the disease.

The Microbiome of Peri-Implantitis: A Systematic Review and Meta-Analysis

This review aimed to systematically compare microbial profiles of peri-implantitis to those of periodontitis and healthy implants. Therefore, an electronic search in five databases was conducted. For inclusion, studies assessing the microbiome of peri-implantitis in otherwise healthy patients were considered. Literature was assessed for consistent evidence of exclusive or predominant peri-implantitis microbiota. Of 158 potentially eligible articles, data of 64 studies on 3730 samples from peri-implant sites were included in this study. Different assessment methods were described in the studies, namely bacterial culture, PCR-based assessment, hybridization techniques, pyrosequencing, and transcriptomic analyses. After analysis of 13 selected culture-dependent studies, no microbial species were found to be specific for peri-implantitis. After assessment of 28 studies using PCR-based methods and a meta-analysis on 19 studies, a higher prevalence of Aggregatibacter actinomycetemcomitans and Prevotella intermedia (log-odds ratio 4.04 and 2.28, respectively) was detected in peri-implantitis biofilms compared with healthy implants. Actinomyces spp., Porphyromonas spp. and Rothia spp. were found in all five pyrosequencing studies in healthy-, periodontitis-, and peri-implantitis samples. In conclusion, the body of evidence does not show a consistent specific profile. Future studies should focus on the assessment of sites with different diagnosis for the same patient, and investigate the complex host-biofilm interaction.

LncRNA-mediated ceRNA network was identified as a crucial determinant of differential effects in periodontitis and periimplantitis by high-throughput sequencing

BACKGROUND AND OBJECTIVE

Although periimplantitis and periodontitis share similar features, particularly clinical features, they are two different diseases and should be analyzed separately. Thus far, few omics-level differences in periimplantitis and periodontitis have been reported. This study was aimed at exploring the differential effects of expression mRNAs, lncRNAs, and miRNAs in periodontitis and periimplantitis by high-throughput sequencing and competitive endogenous RNA (ceRNA) analysis.

METHODS

Gingival tissues of healthy individuals (HI) and periimplantitis (PI) and periodontitis (P) patients were collected and used for genome-wide sequencing. The differentially expressed genes (DEGs) were screened and visualized by R software. The functions and pathways of DEGs were analyzed using Metascape, and the ceRNA network was constructed using the Cytoscape software. Finally, gene set enrichment analysis (GSEA) was used to predict the function of key nodes in ceRNA.

RESULTS AND CONCLUSION

By constructing the regulated ceRNA network, six genes (FAM126B, SORL1, PRLR, CPEB2, RAP2C, and YOD1) and 16 miRNAs (hsa-miR-338-5p, hsa-miR-650, hsa-miR-9-5p, hsa-miR-1290, hsa-miR-544a, hsa-miR-3179, hsa-miR-1269a, hsa-miR-3679-5p, hsa-miR-149-5p, hsa-miR-615-3p, hsa-miR-33b-5p, hsa-miR-31-5p, hsa-miR-4639-5p, hsa-miR-204-5p, hsa-miR-5588-5p, and hsa-mir-196a-5p) were detected. Five long non-coding RNAs (lnc-CORO2B-1, lnc-MBL2-7, lnc-TRIM45-1, lnc-CHST10-2, and lnc-TNP1-6) were found to target these miRNAs in this ceRNA network. The ceRNA network based on transcriptome data revealed that FAM126B, SORL1, PRLR, CPEB2, RAP2C, and YOD1 were crucial proteins of differential effects in periodontitis and periimplantitis. The lncRNA-miRNA-mRNA interaction involved the regulation of the Hippo signaling pathway, Wnt signaling pathway, Toll-like receptor signaling pathway, NOD signaling pathway, oxidative stress, and innate immune process. These regulated pathways and biological processes may be factors contributing to the pathogenesis of periimplantitis being distinct from that of periodontitis.

Persistent colonization of non-lymphoid tissue-resident macrophages by Stenotrophomonas maltophilia

Accumulating evidence has revealed that lymphoid tissue-resident commensal bacteria (e.g. Alcaligenes spp.) survive within dendritic cells. We extended our previous study by investigating microbes that persistently colonize colonic macrophages. 16S rRNA-based metagenome analysis using DNA purified from murine colonic macrophages revealed the presence of Stenotrophomonas maltophilia. The in situ intracellular colonization by S. maltophilia was recapitulated in vitro by using bone marrow-derived macrophages (BMDMs). Co-culture of BMDMs with clinically isolated S. maltophilia led to increased mitochondrial respiration and robust IL-10 production. We further identified a 25-kDa protein encoded by the gene assigned as smlt2713 (recently renamed as SMLT_RS12935) and secreted by S. maltophilia as the factor responsible for enhanced IL-10 production by BMDMs. IL-10 production is critical for maintenance of the symbiotic condition, because intracellular colonization by S. maltophilia was impaired in IL-10-deficient BMDMs, and smlt2713-deficient S. maltophilia failed to persistently colonize IL-10-competent BMDMs. These findings indicate a novel commensal network between colonic macrophages and S. maltophilia that is mediated by IL-10 and smlt2713.

The Role of Bacterial Biofilms in Dental Caries and Periodontal and Peri-implant Diseases: A Historical Perspective

Over the last hundred years, groundbreaking research in oral microbiology has provided a broad and deep understanding about the oral microbiome, its interactions with our body, and how the community can affect our health, be protective, or lead to the development of dental diseases. During this exciting journey, hypotheses were proposed, and concepts were established, discarded, and later revisited from updated perspectives. Dental plaque, previously considered a polymicrobial community of unspecific pathogenicity, is recognized as microbial biofilms with healthy, cariogenic, or periodontopathogenic profiles, resulting from specific ecologic determinants and host factors. The "one pathogen, one disease" paradigm of oral infections has been replaced by a holistic concept of a microbial community as the entity of pathogenicity. Cutting-edge technology can now explore large microbial communities related to different clinical conditions, which has led to finding several novel disease-associated species and potential pathobionts and pathobiomes. This vast amount of data generated over time has widened our view of the etiology of caries and periodontal and peri-implant diseases and has promoted updated strategies to treat and prevent the oral diseases.

Facial alveolar bone alterations and gray value changes based on cone beam computed tomography around maxillary anterior implants: A clinical retrospective study of 1-3 years

OBJECTIVES

The purpose of this cone beam computed tomography (CBCT) study was to describe facial alveolar bone alterations and gray value (GV) changes around implants in aesthetic anterior maxilla with simultaneous guided bone regeneration (GBR) and to investigate potential influence of factors related to vertical alveolar bone stability, such as particle sizes of the deproteinized bovine bone mineral (DBBM) used.

MATERIALS AND METHODS

A retrospective study design was adopted. Four facio-palatal cross-sectional CBCT images of 166 implants from 124 patients who had maxillary anterior implants were obtained. Measurements of the vertical facial alveolar bone level (VFBL), horizontal facial alveolar bone thickness (HFBT), and GV were identified of 1-3 years. Then, correlation coefficients for those parameters were calculated. Finally, linear mixed models were established to investigate potential factors influencing vertical alveolar bone resorption.

RESULTS

Facial alveolar bone underwent fast bone modeling and remodeling during the first 6 months, with decreases of 1.00 ± 1.19 and 0.74 ± 0.86 mm in VFBL and HFBT in implant shoulder, respectively, and there was positive and significant correlation between the alterations in VFBL and HFBT1 (r_s  = .516, p = .000). Linear mixed models identified particle size of DBBM as a critical factor associated with vertical bone resorption (p = .000). The GV gradually increased during the follow-up period.

CONCLUSIONS

Rapid and unavoidable peri-implant bone resorption usually happened during the first 6 months after implant placement. GBR is a predictable treatment for maxillary anterior implants, since GV has an increasing trend. Large bone particles of DBBM help maintain vertical alveolar bone stability.

Emerging Applications of Drug Delivery Systems in Oral Infectious Diseases Prevention and Treatment

The oral cavity is a unique complex ecosystem colonized with huge numbers of microorganism species. Oral cavities are closely associated with oral health and sequentially with systemic health. Many factors might cause the shift of composition of oral microbiota, thus leading to the dysbiosis of oral micro-environment and oral infectious diseases. Local therapies and dental hygiene procedures are the main kinds of treatment. Currently, oral drug delivery systems (DDS) have drawn great attention, and are considered as important adjuvant therapy for oral infectious diseases. DDS are devices that could transport and release the therapeutic drugs or bioactive agents to a certain site and a certain rate in vivo. They could significantly increase the therapeutic effect and reduce the side effect compared with traditional medicine. In the review, emerging recent applications of DDS in the treatment for oral infectious diseases have been summarized, including dental caries, periodontitis, peri-implantitis and oral candidiasis. Furthermore, oral stimuli-responsive DDS, also known as "smart" DDS, have been reported recently, which could react to oral environment and provide more accurate drug delivery or release. In this article, oral smart DDS have also been reviewed. The limits have been discussed, and the research potential demonstrates good prospects.

Long non-coding RNA and mRNA expression profiles in peri-implantitis vs periodontitis

BACKGROUND AND OBJECTIVE

Peri-implantitis is a biofilm-mediated infectious disease that results in progressive loss of implant-supporting bone. As compared to its analogue periodontitis, peri-implantitis is generally known to be more aggressive, with comparatively rapid progression and less predictable treatment outcomes, especially when advanced. An understanding of molecular mechanisms underpinning the similarities and differences between peri-implantitis and periodontitis is essential to develop novel management strategies. This study aimed to compare long non-coding RNAs (lncRNAs) and messenger RNA (mRNA) expression profiles between peri-implantitis and periodontitis.

METHODS

Inflamed soft tissue from peri-implantitis and periodontitis lesions, and healthy gingival tissue controls were analyzed by microarray. Cluster graphs, gene ontology (GO) analysis, and pathway analysis were performed. Quantitative real-time PCR was employed to verify microarray results. The expression levels of RANKL and OPG in the three tissue types were also evaluated, using qRT-PCR. Coding non-coding (CNC) network analyses were performed.

RESULTS

Microarray analyses revealed 1079 lncRNAs and 1003 mRNAs as differentially expressed in peri-implantitis when compared to periodontitis. The cyclooxygenase-2 pathway was the most up-regulated biological process in peri-implantitis as compared to periodontitis, whereas hemidesmosome assembly was the most down-regulated pathway. Osteoclast differentiation was relatively up-regulated, and RANKL/OPG ratio was higher in peri-implantitis than in periodontitis.

CONCLUSIONS

The study demonstrated that peri-implantitis and periodontitis exhibit significantly different lncRNA and mRNA expression profiles, suggesting that osteoclast differentiation-related pathways are comparatively more active in peri-implantitis. These data highlight potential molecular targets for periodontitis and peri-implantitis therapy development.