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Dynamic changes in the subgingival microbiome and their potential for diagnosis and prognosis of periodontitis.

ABSTRACT: UNLABELLED:The human microbiome influences and reflects the health or disease state of the host. Periodontitis, a disease affecting about half of American adults, is associated with alterations in the subgingival microbiome of individual tooth sites. Although it can be treated, the disease can reoccur and may progress without symptoms. Without prognostic markers, follow-up examinations are required to assess reoccurrence and disease progression and to determine the need for additional treatments. To better identify and predict the disease progression, we aim to determine whether the subgingival microbiome can serve as a diagnosis and prognosis indicator. Using metagenomic shotgun sequencing, we characterized the dynamic changes in the subgingival microbiome in periodontitis patients before and after treatment at the same tooth sites. At the taxonomic composition level, the periodontitis-associated microorganisms were significantly shifted from highly correlated in the diseased state to poorly correlated after treatment, suggesting that coordinated interactions among the pathogenic microorganisms are essential to disease pathogenesis. At the functional level, we identified disease-associated pathways that were significantly altered in relative abundance in the two states. Furthermore, using the subgingival microbiome profile, we were able to classify the samples to their clinical states with an accuracy of 81.1%. Follow-up clinical examination of the sampled sites supported the predictive power of the microbiome profile on disease progression. Our study revealed the dynamic changes in the subgingival microbiome contributing to periodontitis and suggested potential clinical applications of monitoring the subgingival microbiome as an indicator in disease diagnosis and prognosis. IMPORTANCE:Periodontitis is a common oral disease. Although it can be treated, the disease may reoccur without obvious symptoms. Current clinical examination parameters are useful in disease diagnosis but cannot adequately predict the outcome of individual tooth sites after treatment. A link between the subgingival microbiota and periodontitis was identified previously; however, it remains to be investigated whether the microbiome can serve as a diagnostic and prognostic indicator. In this study, for the first time, we characterized the subgingival microbiome of individual tooth sites before and after treatment using a large-scale metagenomic analysis. Our longitudinal study revealed changes in the microbiota in taxonomic composition, cooccurrence of subgingival microorganisms, and functional composition. Using the microbiome profiles, we were able to classify the clinical states of subgingival plaque samples with a high accuracy. Follow-up clinical examination of sampled sites indicates that the subgingival microbiome profile shows promise for the development of diagnostic and prognostic tools.

SUBMITTER: Shi B

PROVIDER: S-EPMC4337560 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Dynamic changes in the subgingival microbiome and their potential for diagnosis and prognosis of periodontitis.

Shi Baochen B Chang Michaela M Martin John J Mitreva Makedonka M Lux Renate R Klokkevold Perry P Sodergren Erica E Weinstock George M GM Haake Susan K SK Li Huiying H

mBio 20150217 1

<h4>Unlabelled</h4>The human microbiome influences and reflects the health or disease state of the host. Periodontitis, a disease affecting about half of American adults, is associated with alterations in the subgingival microbiome of individual tooth sites. Although it can be treated, the disease can reoccur and may progress without symptoms. Without prognostic markers, follow-up examinations are required to assess reoccurrence and disease progression and to determine the need for additional tr ...[more]

PMID: 25691586

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

Project description:Chronic periodontitis is an inflammatory disease of the periodontium affecting nearly 65 million adults in the United States. Changes in subgingival microbiota have long been associated with chronic periodontitis. Recent culture-independent molecular studies have revealed the immense richness and complexity of oral microbial communities. However, data sets across studies have not been directly compared, and whether the observed microbial variations are consistent across different studies is not known. Here, we used 16S rRNA sequencing to survey the subgingival microbiota in 25 subjects with chronic periodontal disease and 25 healthy controls and compared our data sets with those of three previously reported microbiome studies. Consistent with data from previous studies, our results demonstrate a significantly altered microbial community structure with decreased heterogeneity in periodontal disease. Comparison with data from three previously reported studies revealed that subgingival microbiota clustered by study. However, differences between periodontal health and disease were larger than the technical variations across studies. Using a prediction score and applying five different distance metrics, we observed two predominant clusters. One cluster was driven by Fusobacterium and Porphyromonas and was associated with clinically apparent periodontitis, and the second cluster was dominated by Rothia and Streptococcus in the majority of healthy sites. The predicted functional capabilities of the periodontitis microbiome were significantly altered. Genes involved in bacterial motility, energy metabolism, and lipopolysaccharide biosynthesis were overrepresented in periodontal disease, whereas genes associated with transporters, the phosphotransferase system, transcription factors, amino acid biosynthesis, and glycolysis/gluconeogenesis were enriched in healthy controls. These results demonstrate significant alterations in microbial composition and function in periodontitis and suggest genes and metabolic pathways associated with periodontal disease.

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

Project description:No microbiological criteria were included in the 2018 EFP-AAP classification of periodontal diseases that could be used to differentiate between stages and grades. Furthermore, differences in the subgingival microbiome depending on stage and grade have not been established. Sixty subgingival biofilm samples were collected in Spain (n = 30) and Colombia (n = 30) from three distinct patient categories: those with periodontal health/gingivitis (n = 20), those with stage I-II periodontitis (n = 20), and those with stage III-IV periodontitis (n = 20). Patients were evaluated by 16S rRNA gene amplification sequencing. Amplicon sequence variants were used to assign taxonomic categories compared to the Human Oral Microbiome Database (threshold ≥97% identity). Alpha diversity was established by Shannon and Simpson indices, and principal coordinate analysis, ANOSIM, and PERMANOVA of the UNIFRAC distances were performed using QIIME2. Although differences in the alpha diversity were observed between samples according to country, Filifactor alocis, Peptostreptococcaceae [XI][G-4] bacterium HMT 369, Fretibacterium fastidiosum, Lachnospiraceae [G-8] bacterium HMT 500, Peptostreptococcaceae [XI][G-5] [Eubacterium] saphenum, Peptostreptococcus stomatis, and Tannerella forsythia were associated with periodontitis sites in all stages. However, only F. alocis, Peptostreptococcaceae [XI][G-4] bacterium HMT 369, Peptostreptococcaceae [XI][G-9] [Eubacterium] brachy, Peptostreptococcaceae [XI][G-5] [Eubacterium] saphenum, and Desulfobulbus sp. HMT 041 were consistent in stage III-IV periodontitis in both countries. Porphyromonas gingivalis and Tannerella forsythia were differentially expressed in severe lesions in the countries studied. Although some non-cultivable microorganisms showed differential patterns between the different stages of periodontitis, they were not the same in the two countries evaluated. Further studies using larger samples with advanced next-generation techniques for high-throughput sequencing of phyla and non-cultivable bacteria within the subgingival microbiome could provide more insight into the differences between stages of periodontitis.

Project description:Periodontitis is a kind of infectious disease initiated by colonization of subgingival periodontal pathogens, which cause destruction of tooth-supporting tissues, and is a predominant threat to oral health as the most common cause of loss of teeth. The aim of this pilot study was to characterize the subgingival bacterial biodiversity of periodontal pockets with different probing depths in patients with different forms of periodontitis. Twenty-one subgingival plaque samples were collected from three patients with chronic periodontitis (ChP), three patients with aggressive periodontitis (AgP) and three periodontally healthy subjects (PH). Each patient with periodontitis was sampled at three sites, at different probing depths (PDs, one each at 4 mm, 5-6 mm, and ≥ 7 mm). Using 16S rRNA gene high-throughput sequencing and bioinformatic analysis, we found that subgingival communities in health and periodontitis samples largely differed. Meanwhile, Acholeplasma, Fretibacterium, Porphyromonas, Peptococcus, Treponema_2, Defluviitaleaceae_UCG_011, Filifactor, and Mycoplasma increased with the deepening of the pockets in ChP, whilst only Corynebacterium was negatively associated with PD. In AgP, Corynebacterium and Klebsiella were positively associated with PD, while Serratia, Pseudoramibacter, Defluviitaleaceae_UCG_011, and Desulfobulbus were negatively associated with PD. And among these two groups, Corynebacterium shifted differently. Moreover, in subgingival plaque, the unweighted UniFrac distances between samples from pockets with different PD in the same patients were significantly lower than those from pockets within the same PD category from different patients. This study demonstrated the shift of the subgingival microbiome in individual teeth sites during disease development. Within the limitation of the relative small sample size, this pilot study shed new light on the dynamic relationship between the extent of periodontal destruction and the subgingival microbiome.

Dataset Information

Dynamic changes in the subgingival microbiome and their potential for diagnosis and prognosis of periodontitis.

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Dynamic changes in the subgingival microbiome and their potential for diagnosis and prognosis of periodontitis.

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