Do different probing depths exhibit striking differences in microbial profiles?

Pérez-Chaparro, Paula Juliana; McCulloch, John Anthony; Mamizuka, Elsa Masae; Moraes, Aline da Costa Lima; Faveri, Marcelo; Figueiredo, Luciene Cristina; Duarte, Poliana Mendes; Feres, Magda

doi:10.1111/jcpe.12811

Cited by 51 publications

(59 citation statements)

References 45 publications

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“…Second, our sampling strategy called for collection of four subgingival plaque samples (each harvested from the mesio-lingual surface of the most posterior tooth in each quadrant) which were subsequently pooled into a single sample/participant. Given the established association between PD and microbial profiles, 8,[35][36][37] the mesiolingual, rather than the commonly used mesio-buccal site was purposefully selected to avoid microbial sampling from shallower pockets due to gingival recession. Importantly, our data showed that the probing depths of the sampled sites were, on average, deeper than, but strongly positively correlated with, the whole mouth scores.…”

Section: Discussionmentioning

confidence: 99%

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

Papapanou¹,

Park

Cheng

et al. 2020

Journal of Periodontology

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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 DADA2based 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.

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Section: Discussionmentioning

confidence: 99%

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

Papapanou¹,

Park

Cheng

et al. 2020

Journal of Periodontology

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“…In recent years, NGS has been widely used to analyze subgingival bacterial composition and to characterize compositional shifts between periodontal health and disease (Liu et al, 2012 ; Abusleme et al, 2013 ; Li et al, 2015 ; Park et al, 2015 ; Han et al, 2017 ). Some studies observed the striking differences between the microbiota of healthy sites (probing depth ≤ 3 mm) and diseased sites in ChP subjects (Ge et al, 2013 ; Pérez-Chaparro et al, 2018 ), as it is known that the composition of the subgingival microbiome varies according to probing depths possibly because of dissimilar ecological parameters such as oxygen tension (Loesche et al, 1983 ; Abusleme et al, 2013 ). However, there is scarce evidence on the shift of subgingival microbiome in individual tooth sites of both types of periodontitis during disease development.…”

Section: Introductionmentioning

confidence: 99%

The Subgingival Microbiome of Periodontal Pockets With Different Probing Depths in Chronic and Aggressive Periodontitis: A Pilot Study

Shi

Wei

et al. 2018

Front. Cell. Infect. Microbiol.

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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.

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“…7 Up to 15 taxa could be differentiated simultaneously using combinatorial labeling and the spectral imaging-FISH technique, whereas this number is still very limited compared with that of more than 200 taxa that have been detected in subgingival plaques. [8][9][10][11] The other barrier in the subgingival plaque structure study is in the mature subgingival plaque accessing, particularly for the surface layer. 12 Until now, tooth extraction is the only method to obtain undisturbed natural subgingival plaques, which is unrepeatable and could only be applied to a hopeless tooth.…”

Section: Introductionmentioning

confidence: 99%

Measuring the subgingival microbiota in periodontitis patients: Comparison of the surface layer and the underlying layers

Liu

Chen

Cai

et al. 2019

Microbiology and Immunology

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Periodontitis is a major cause of tooth loss in adults that initially results from dental plaque. Subgingival plaque pathogenesis is affected by both community composition and plaque structures, although limited data are available concerning the latter. To bridge this knowledge gap, subgingival plaques were obtained using filter paper (the fourth layer) and curette (the first-third layers) sequentially and the phylogenetic differences between the first-third layers and the fourth layer were characterized by sequencing the V3-V4 regions of 16S rRNA. A total of 11 phyla, 148 genera, and 308 species were obtained by bioinformatic analysis, and no significant differences between the operational taxonomic unit numbers were observed for these groups. In both groups, the most abundant species were Porphyromonas gingivalis and Fusobacterium nucleatum. Actinomyces naeslundii, Streptococcus intermedius, and Prevotella intermedia possessed relatively high proportions in the first-third layers; while in the fourth layer, both traditional pathogens (Treponema denticola and Campylobacter rectus) and novel pathobionts (Eubacterium saphenum, Filifactor alocis, Treponema sp. HOT238) were prominent. Network analysis showed that either of them exhibited a scale-free property and was constructed by two negatively correlated components (the pathogen component and the nonpathogen component), while the synergy in the nonpathogen component was lower in the first-third layers than that in the fourth layer. After merging these two parts into a whole plaque group, the negative/positive correlation ratio increased. With potential connections, the first-third layers and the fourth layer showed characteristic key nodes in bacterial networks. K E Y W O R D Speriodontitis, plaque layers, sequencing, subgingival microbiota Abbreviations: ANCOVA, analysis of covariance; ANOSIM, analysis of the similarities; BI, bleeding index; CAL, clinical attachment loss; FISH, fluorescent in situ hybridization; LDA, linear discriminant analysis; LEfSe, linear discriminant analysis effect size; OTU, operational taxonomic unit; PCoA, principal coordinate analysis; PD, probing depth; PlI, plaque index.

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Do different probing depths exhibit striking differences in microbial profiles?

Cited by 51 publications

References 45 publications

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

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

The Subgingival Microbiome of Periodontal Pockets With Different Probing Depths in Chronic and Aggressive Periodontitis: A Pilot Study

Measuring the subgingival microbiota in periodontitis patients: Comparison of the surface layer and the underlying layers

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