Subgingival Microbiota and Cytokines Profile Changes in Patients with Periodontitis: A Pilot Study Comparing Healthy and Diseased Sites in the Same Oral Cavities

Assessing peri-implant bacterial community structure: the effect of microbiome sample collection method

BACKGROUND

Oral microbiota comprises polymicrobial communities shaped by mutualistic coevolution with the host, contributing to homeostasis and regulating immune function. Nevertheless, dysbiosis of oral bacterial communities is associated with a number of clinical symptoms that ranges from infections to oral cancer. Peri-implant diseases are biofilm-associated inflammatory conditions affecting the soft and hard tissues around dental implants. Characterization and identification of the biofilm community are essential for the understanding of the pathophysiology of such diseases. For that sampling methods should be representative of the biofilm communities Therefore, there is a need to know the effect of different sampling strategies on the biofilm characterization by next generation sequencing.

METHODS

With the aim of selecting an appropriate microbiome sampling procedure for periimplant biofilms, next generation sequencing was used for characterizing the bacterial communities obtained by three different sampling strategies two months after transepithelial abutment placement: adjacent periodontal crevicular fluid (ToCF), crevicular fluid from transepithelial abutment (TACF) and transepithelial abutment (TA).

RESULTS

Significant differences in multiple alpha diversity indices were detected at both the OTU and the genus level between different sampling procedures. Differentially abundant taxa were detected between sample collection strategies, including peri-implant health and disease related taxa. At the community level significant differences were also detected between TACF and TA and also between TA and ToCF. Moreover, differential network properties and association patterns were identified.

CONCLUSIONS

The selection of sample collection strategy can significantly affect the community composition and structure.

TRIAL REGISTRATION

This research is part of a randomized clinical trial that was designed to assess the effect of transepithelial abutment surface on the biofilm formation. The trial was registered at Trial Registration ClinicalTrials.gov under the number NCT03554876.

Progression from healthy periodontium to gingivitis and periodontitis: Insights from bioinformatics-driven proteomics - A systematic review with meta-analysis

AIM

The current study aimed to: (1) systematically review the published literature regarding the proteomics analyses of saliva and gingival crevicular fluid (GCF) in healthy humans and gingivitis and/or periodontitis patients; and (2) to identify the differentially expressed proteins (DEPs) based on the systematic review, and comprehensively conduct meta-analyses and bioinformatics analyses.

METHODS

An online search of Web of Science, Scopus, and PubMed was performed without any restriction on the year and language of publication. After the identification of the DEPs reported by the included human primary studies, gene ontology (GO), the Kyoto encyclopedia of genes and genomes pathway (KEGG), protein-protein interaction (PPI), and meta-analyses were conducted. The risk of bias among the included studies was evaluated using the modified Newcastle-Ottawa quality assessment scale.

RESULTS

The review identified significant differences in protein expression between healthy individuals and those with gingivitis and periodontitis. In GCF, 247 proteins were upregulated and 128 downregulated in periodontal diseases. Saliva analysis revealed 79 upregulated and 70 downregulated proteins. There were distinct protein profiles between gingivitis and periodontitis, with 159 and 31 unique upregulated proteins in GCF, respectively. Meta-analyses confirmed significant upregulation of various proteins in periodontitis, including ALB and MMP9, while CSTB and GSTP1 were downregulated. AMY1A and SERPINA1 were upregulated in periodontitis saliva. HBD was upregulated in gingivitis GCF, while DEFA3 was downregulated. PPI analysis revealed complex networks of interactions among DEPs. GO and KEGG pathway analyses provided insights into biological processes and pathways associated with periodontal diseases.

CONCLUSION

The ongoing MS-based proteomics studies emphasize the need for a highly sensitive and specific diagnostic tool for periodontal diseases. Clinician acceptance of the eventual diagnostic method relies on its ability to provide superior or complementary information to current clinical assessment procedures. Future research should prioritize the multiplex measurement of multiple biomarkers simultaneously to enhance diagnostic accuracy and large study cohorts are necessary to ensure the validity and reliability of research findings.

Extracellular host DNA contributes to pathogenic biofilm formation during periodontitis

Introduction

Periodontal diseases are known to be associated with polymicrobial biofilms and inflammasome activation. A deeper understanding of the subgingival cytological (micro) landscape, the role of extracellular DNA (eDNA) during periodontitis, and contribution of the host immune eDNA to inflammasome persistence, may improve our understanding of the mechanisms underlaying severe forms of periodontitis.

Methods

In this work, subgingival biolfilms developing on biologically neutral polyethylene terephthalate films placed in gingival cavities of patients with chronic periodontitis were investigated by confocal laser scanning microscopy (CLSM). This allowed examination of realistic cytological landscapes and visualization of extracellular polymeric substances (EPS) including amyloids, total proteins, carbohydrates and eDNA, as well as comparison with several single-strain in vitro model biofilms produced by oral pathogens such as Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus gordonii, S. sanguinis and S. mitis. Fluorescence in situ hybridization (FISH) analysis was also used to identify eDNA derived from eubacteria, streptococci and members of the Bacteroides-Porphyromonas-Prevotella (BPP) group associated with periodontitis.

Results

Analysis of subgingival biofilm EPS revealed low levels of amyloids and high levels of eDNA which appears to be the main matrix component. However, bacterial eDNA contributed less than a third of the total eDNA observed, suggesting that host-derived eDNA released in neutrophil extracellular traps may be of more importance in the development of biofilms causing periodontitis.

Discussion

eDNA derived from host immunocompetent cells activated at the onset of periodontitis may therefore be a major driver of bacterial persistence and pathogenesis.

Analysis of subgingival microbiota and IL-1β, TNF-α and CX3CL1 levels in gingival crevicular fluid of fixed dental prostheses

Prosthetic biomaterials can affect the composition of the subgingival microbiota and consequently the production of proinflammatory cytokines, causing damage to the periodontium. A total of 40 patients were divided into two groups: 20 with monolithic zirconia (MZ) prostheses and 20 with porcelain fused to metal (PFM) with nickel-chromium (Ni-Cr) alloy prostheses. Subgingival plaque and gingival crevicular fluid samples were taken. The Checkerboard technique for DNA-DNA hybridization and the enzyme-linked immunosorbent assay technique were performed. Teeth with MZ presented a lower percentage of bleeding on probing and tooth mobility compared to teeth with PFM with Ni-Cr alloy. Prosthodontic teeth harbored higher total levels of the 18 bacterial species than non-prosthodontic teeth. There was a higher prevalence of S. gordonii and V. parvula species in PFM with Ni-Cr alloy compared to MZ. There was an increase in IL-1β, TNF-α and CX3CL1 levels in PFM with Ni-Cr alloy compared to MZ. MZ is a candidate biomaterial with fewer negative effects on the periodontium, allowing for longer prostheses longevity in the mouth.

Influence of obesity on subgingival microbiota composition in subjects with different periodontal status: a systematic review

Objective

This systematic review aimed to investigate the changes in the composition of the subgingival microbiota among subjects with normo-weight, overweight and obesity, in conditions of periodontal health and disease.

Materials and Methods

The protocol for this study was designed following PRISMA guidelines. Records were identified using different search engines (PubMed/MedLine, Scopus and Web of Science). Observational studies, in human subjects diagnosed with obesity (BMI >30kg/m2) and periodontal disease (gingivitis and periodontitis), on the analysis of subgingival microbiota were selected. Eight articles were included.

Results

The subgingival microbiota of 1,229 subjects (n=894 exposure group and n=335 control group) was analyzed. Periodontal pathogens were the most common bacteria detected in subjects with obesity and periodontitis (Porphyromonas gingivalis, Tannerella forsythia, Campylobacter gracilis, Eubacterium nodatum, Fusobacterium nucleatum spp. vincentii, Parvimonas micra, Prevotella intermedia, Campylobacter rectus, and Aggregatibacter actinomycetemcomitans), as along with some accessory pathogens such as: Streptococcus gordonii, and Veillonella parvula that favor the virulence of late colonizers.

Conclusions

Although there are evident alterations in the composition of the subgingival microbiota in subjects with obesity and periodontitis, it is still a challenge to identify a specific pattern of microbiota in these subjects. If associations between subgingival plaque microorganisms and obesity are confirmed, microbiome analysis could be a useful tool to improve preventive measures and the management of people with obesity.

Subgingival microbiome in periodontal health, gingivitis and different stages of periodontitis

AIM

To characterize the subgingival microbiome in subjects with different periodontal health statuses.

MATERIALS AND METHODS

In this cross-sectional observational study, subgingival samples were harvested from Spanish subjects with different periodontal health statuses, based on the 2018 Classification of Periodontal and Peri-Implant Diseases and Conditions. Samples were processed using high-throughput sequencing technologies (Illumina MiSeq). Taxa differentially abundant were identified using Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC). α- and β-diversity metrics were calculated using q2-diversity in QIIME2. The analyses were adjusted for age, gender and smoking status.

RESULTS

The identified subgingival microbiome showed statistically significant differences among subjects, categorized into periodontal health, gingivitis and stages I-II and III-IV periodontitis (p < .05). In patients with severe (stages III-IV) periodontitis, the genera Filifactor and Fretibacterium were detected 24 times more frequently than in periodontally healthy subjects. Similarly, the genera Porphyromonas, Prevotella and Tannerella were detected four times more frequently (p < .05). The genera Granulicatella, Streptococcus, Paracoccus, Pseudomonas, Haemophilus, Actinobacteria, Bergeyella and Capnocytophaga were significantly associated with healthier periodontal status (p < .05).

CONCLUSIONS

Significant differences were detected in the subgingival microbiome among periodontal health, gingivitis and stages I-II or III-IV periodontitis, suggesting overlapping, yet distinguishable microbial profiles.

The oral microbiome in autoimmune diseases: friend or foe?

The human body is colonized by abundant and diverse microorganisms, collectively known as the microbiome. The oral cavity has more than 700 species of bacteria and consists of unique microbiome niches on mucosal surfaces, on tooth hard tissue, and in saliva. The homeostatic balance between the oral microbiota and the immune system plays an indispensable role in maintaining the well-being and health status of the human host. Growing evidence has demonstrated that oral microbiota dysbiosis is actively involved in regulating the initiation and progression of an array of autoimmune diseases.Oral microbiota dysbiosis is driven by multiple factors, such as host genetic factors, dietary habits, stress, smoking, administration of antibiotics, tissue injury and infection. The dysregulation in the oral microbiome plays a crucial role in triggering and promoting autoimmune diseases via several mechanisms, including microbial translocation, molecular mimicry, autoantigen overproduction, and amplification of autoimmune responses by cytokines. Good oral hygiene behaviors, low carbohydrate diets, healthy lifestyles, usage of prebiotics, probiotics or synbiotics, oral microbiota transplantation and nanomedicine-based therapeutics are promising avenues for maintaining a balanced oral microbiome and treating oral microbiota-mediated autoimmune diseases. Thus, a comprehensive understanding of the relationship between oral microbiota dysbiosis and autoimmune diseases is critical for providing novel insights into the development of oral microbiota-based therapeutic approaches for combating these refractory diseases.

Potential Impact of Prosthetic Biomaterials on the Periodontium: A Comprehensive Review

The success of a prosthetic treatment is closely related to the periodontal health of the individual. The aim of this article was to review and present the importance of prosthetic restorative materials on the condition of the periodontium, the changes that occur in the composition of the subgingival microbiota and the levels of inflammatory markers in gingival crevicular fluid. Articles on the influence of different prosthetic restorative materials on subgingival microbiota and proinflammatory cytokines were searched for using the keywords "prosthetic biomaterials", "fixed prosthesis", "periodontal health", "subgingival microbiota", "periodontal biomarkers" and "gingival crevicular fluid" in PubMed/Medline, Science Direct, Scopus and Google Scholar. The type of material used for prosthesis fabrication together with poor marginal and internal fit can result in changes in the composition of the subgingival microbiota, as well as increased accumulation and retention of dentobacterial plaque, thus favoring the development of periodontal disease and prosthetic treatment failure. Biological markers have helped to understand the inflammatory response of different prosthetic materials on periodontal tissues with the main purpose of improving their clinical application in patients who need them. Metal-free ceramic prostheses induce a lower inflammatory response regardless of the fabrication method; however, the use of CAD/CAM systems is recommended for their fabrication. In addition, it is presumed that metal-ceramic prostheses cause changes in the composition of the subgingival microbiota producing a more dysbiotic biofilm with a higher prevalence of periodontopathogenic bacteria, which may further favor periodontal deterioration.

Salivary Microbiome Profile of Diabetes and Periodontitis in a Chinese Population

Aim

There is a bidirectional association between diabetes and periodontitis. However, the effect of diabetes on the periodontitis salivary microbiota has not been elucidated. The aim of this study was to determine the effect of the presence of diabetes on the microbiota among Chinese patients with periodontitis.

Materials and Methods

Unstimulated whole saliva samples were collected from the periodontitis with diabetes group (TC), chronic periodontitis group (CP), and periodontally healthy and systemically healthy group (H) by spitting method. Bacterial genomic DNA was PCR-amplified at the V4 variable region of 16S rRNA gene. The library was constructed according to the obtained sequence results, and biological analysis and statistical analysis were carried out. Functional prediction of three groups of microbial communities was performed by the PICRUSt algorithm.

Results

There was no significant difference in bacterial diversity between the TC and CP groups. Compared with the H group, the TC group and CP group presented a higher diversity of salivary flora. Firmicutes, Streptococcus, Haemophilus, Veillonella, and Haemophilus parainfluenzae dominated the H group. Corynebacterium, Leptotrichia, Dialister, Comamonas, Capnocytophaga, Catonella, Filifactor, Campylobacter, Treponema, Campylobacter concisus, Prevotella oralis, and Porphyromonas gingivalis were significantly enriched in the TC and CP groups. Among them, Treponema and P. oralis were the most abundant in the TC group. The PICRUSt results showed that many pathways related to cell motility and functional metabolism of the salivary microbial flora changed in the TC group and the CP group.

Conclusions

Diabetes was not the main factor causing the altered diversity of salivary microbiota in patients with periodontitis; however, the presence of diabetes altered the abundance of some microbiota in saliva.