A longitudinal assessment of changes in bacterial community composition associated with the development of periodontal disease in dogs.
TL;DR: This is the first study to demonstrate the temporal dynamics of the canine oral microbiota; it showed that periodontitis results from a microbial succession predominantly characterised by a reduction of previously abundant, health associated taxa.
About: This article is published in Veterinary Microbiology.The article was published on 2015-12-31 and is currently open access. It has received 55 citations till now. The article focuses on the topics: Periodontitis & Gingivitis.
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TL;DR: The information provided in this review can be used by veterinarians to improve the effectiveness of their diagnosis, treatments and interventions by focussing their efforts on the sizes, breeds and individuals most at risk.
Abstract: Periodontal disease is a frequent problem seen in veterinary practices. Primary-care veterinary practices, where diagnosis of periodontal disease is predominantly based on visual oral assessment of conscious dogs, report an average prevalence of 9.3 to 18.2% within the dog population. Detailed examinations of anaesthetised dogs report much higher prevalence of between 44 and 100%. The prevalence and severity of periodontitis varies between sizes of dogs, breeds and individuals. The lack of robust evaluation of these variances opens the opportunity for a review of the topic. A literature search was therefore undertaken to determine the frequency and extent (severity and oral location) of periodontal disease in the dog population. Both clinical and retrospective data based surveys of veterinary records, show there is an increased likelihood of developing periodontitis as age increases and with bodyweight decreases. The maxillary and mandibular incisors, fourth premolars and first molars are likely to develop the disease first although in some breeds the canines may also be involved. Poor oral care is a significant risk factor for the development of periodontal disease although diet, behaviour, environment and genetics are also likely to play a role. The information provided in this review can be used by veterinarians to improve the effectiveness of their diagnosis, treatments and interventions by focussing their efforts on the sizes, breeds and individuals most at risk. Given the potential link between periodontal disease and systemic health, veterinarians have the opportunity to positively impact the quality of life of a large number of dogs and therefore their owners.
42 citations
TL;DR: The findings suggest that EGCG interacts with other component(s) of the bacterial membrane aside from streptococcal LTA to inhibit biofilm formation and damage biofilms.
Abstract: Epigallocatechin gallate (EGCG) is the major polyphenolic compound of green tea. Polyphenolic compounds were extracted from the leaf of Camellia sinensis (Japanese green tea), and the minimum inhibitory concentration against canine oral bacteria was measured. Subsequently, we investigated the inhibitory effects of polyphenolic compounds and EGCG on the growth of canine oral bacteria. EGCG showed antimicrobial activity against a model bacterium, Streptococcus mutans. Our results indicate that EGCG can inhibit the growth and biofilm formation of S. mutans and that EGCG does not interact with streptococcal lipoteichoic acid (LTA). Furthermore, our findings suggest that EGCG interacts with other component(s) of the bacterial membrane aside from streptococcal LTA to inhibit biofilm formation and damage biofilms.
35 citations
Cites background from "A longitudinal assessment of change..."
...It has been reported that oral disorders, such as periodontitis, occur frequently in dogs [15, 16, 33]....
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TL;DR: The ability to distinguish the niches by their microbiota signature offers the potential for microbial biomarkers to be identified in each unique niche for diagnostic use.
Abstract: Microbiota from different niches within the canine oral cavity were profiled and compared. Supragingival plaque and stimulated saliva, were collected alongside samples from the buccal and tongue dorsum mucosa, from 14 Labrador retrievers at three timepoints within a 1 month timeframe. The V3-V4 region of the 16S rRNA gene was sequenced via Illumina MiSeq. Supragingival plaque microbiota had the highest bacterial diversity and the largest number of significant differences in individual taxa when compared to the other oral niches. Stimulated saliva exhibited the highest variability in microbial composition between dogs, yet the lowest bacterial diversity amongst all the niches. Overall, the bacteria of the buccal and tongue dorsum mucosa were most similar. The bacterial community profiles indicated three discrete oral niches: soft tissue surfaces (buccal and tongue dorsum mucosa), hard tissue surface (supragingival plaque) and saliva. The ability to distinguish the niches by their microbiota signature offers the potential for microbial biomarkers to be identified in each unique niche for diagnostic use.
34 citations
TL;DR: Direct RT-SSU rRNA sequencing revealed that 16S rRNA molecules belonging to the bacterial phyla Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria and Spirochaetes were most abundant in the canine oral microbiome, and this demonstrated the veracity of direct RT- SSU r RNA sequencing for molecular microbial ecology.
Abstract: PCR amplification and sequencing of phylogenetic markers, primarily Small Sub-Unit ribosomal RNA (SSU rRNA) genes, has been the paradigm for defining the taxonomic composition of microbiomes. However, ‘universal’ SSU rRNA gene PCR primer sets are likely to miss much of the diversity therein. We sequenced a library comprising purified and reverse-transcribed SSU rRNA (RT-SSU rRNA) molecules from the canine oral microbiome and compared it to a general bacterial 16S rRNA gene PCR amplicon library generated from the same biological sample. In addition, we have developed BIONmeta, a novel, open-source, computer package for the processing and taxonomic classification of the randomly fragmented RT-SSU rRNA reads produced. Direct RT-SSU rRNA sequencing revealed that 16S rRNA molecules belonging to the bacterial phyla Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria and Spirochaetes, were most abundant in the canine oral microbiome (92.5% of total bacterial SSU rRNA). The direct rRNA sequencing approach detected greater taxonomic diversity (1 additional phylum, 2 classes, 1 order, 10 families and 61 genera) when compared with general bacterial 16S rRNA amplicons from the same sample, simultaneously provided SSU rRNA gene inventories of Bacteria, Archaea and Eukarya, and detected significant numbers of sequences not recognised by ‘universal’ primer sets. Proteobacteria and Spirochaetes were found to be under-represented by PCR-based analysis of the microbiome, and this was due to primer mismatches and taxon-specific variations in amplification efficiency, validated by qPCR analysis of 16S rRNA amplicons from a mock community. This demonstrated the veracity of direct RT-SSU rRNA sequencing for molecular microbial ecology.
33 citations
Cites background or result from "A longitudinal assessment of change..."
...5 [33,34], whilst this almost reverses in the RT-SSU rRNA data set (Fig 1)....
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...Previous studies [33,34] using PCR amplification and highthroughput sequencing to characterize the microbial composition of canine subgingival plague have identified high numbers of Gram negative bacteria associated with health, and a shift to Gram positive communities with the onset of disease [33,34]....
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TL;DR: The findings corroborate those in the current literature regarding the complexity of the subgingival microbiota of the domestic cat and reveal both differences and similarities among periodontally healthy and diseased cats.
Abstract: Periodontitis is a common and important health problem in domestic cats. The subgingival microbiota of cats diagnosed with chronic periodontitis (CP), aggressive periodontitis (AP), and feline chronic gingivostomatitis (FCGS) are not well characterized. Thus, the aim of the present study was to characterize and compare the periodontal microbiota of periodontally healthy cats versus cats diagnosed with CP, AP, and FCGS by using next-generation sequencing. In total, 44 domestic cats were enrolled, and 139 subgingival samples were subjected to 16S rRNA gene sequencing to investigate the microbiota composition of each periodontal group evaluated. Our results identified several key genera previously described in periodontal disease (e.g. Treponema and Filifactor) and in the oral microbiota (e.g. Moraxella and Capnocytophaga) of healthy cats. Phylogenetic beta diversity analysis showed that the microbiota of periodontally healthy cats were distinguishable from diseased cats. Even though most of the genera known to be associated with periodontal disease were also identified in healthy cats, they were present at significantly lower relative abundance. Remarkably, alpha diversity was found to be higher in the disease groups compared to healthy animals. These results suggest a pathological mechanism involving opportunistic behavior. Our findings corroborate those in the current literature regarding the complexity of the subgingival microbiota of the domestic cat and reveal both differences and similarities among periodontally healthy and diseased cats.
28 citations
References
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TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Abstract: SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
83,420 citations
TL;DR: A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original.
Abstract: The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
70,111 citations
TL;DR: An overview of the analysis pipeline and links to raw data and processed output from the runs with and without denoising are provided.
Abstract: Supplementary Figure 1 Overview of the analysis pipeline. Supplementary Table 1 Details of conventionally raised and conventionalized mouse samples. Supplementary Discussion Expanded discussion of QIIME analyses presented in the main text; Sequencing of 16S rRNA gene amplicons; QIIME analysis notes; Expanded Figure 1 legend; Links to raw data and processed output from the runs with and without denoising.
28,911 citations
TL;DR: SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains.
Abstract: Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs.
5,733 citations
TL;DR: The purpose of the present investigation was to attempt to define communities using data from large numbers of plaque samples and different clustering and ordination techniques, which related strikingly to clinical measures of periodontal disease particularly pocket depth and bleeding on probing.
Abstract: It has been recognized for some time that bacterial species exist in complexes in subgingival plaque. The purpose of the present investigation was to attempt to define such communities using data from large numbers of plaque samples and different clustering and ordination techniques. Subgingival plaque samples were taken from the mesial aspect of each tooth in 185 subjects (mean age 51 +/- 16 years) with (n = 160) or without (n = 25) periodontitis. The presence and levels of 40 subgingival taxa were determined in 13,261 plaque samples using whole genomic DNA probes and checkerboard DNA-DNA hybridization. Clinical assessments were made at 6 sites per tooth at each visit. Similarities between pairs of species were computed using phi coefficients and species clustered using an averaged unweighted linkage sort. Community ordination was performed using principal components analysis and correspondence analysis. 5 major complexes were consistently observed using any of the analytical methods. One complex consisted of the tightly related group: Bacteroides forsythus, Porphyromonas gingivalis and Treponema denticola. The 2nd complex consisted of a tightly related core group including members of the Fusobacterium nucleatum/periodonticum subspecies, Prevotella intermedia, Prevotella nigrescens and Peptostreptococcus micros. Species associated with this group included: Eubacterium nodatum, Campylobacter rectus, Campylobacter showae, Streptococcus constellatus and Campylobacter gracilis. The 3rd complex consisted of Streptococcus sanguis, S. oralis, S. mitis, S. gordonii and S. intermedius. The 4th complex was comprised of 3 Capnocytophaga species, Campylobacter concisus, Eikenella corrodens and Actinobacillus actinomycetemcomitans serotype a. The 5th complex consisted of Veillonella parvula and Actinomyces odontolyticus. A. actinomycetemcomitans serotype b, Selenomonas noxia and Actinomyces naeslundii genospecies 2 (A. viscosus) were outliers with little relation to each other and the 5 major complexes. The 1st complex related strikingly to clinical measures of periodontal disease particularly pocket depth and bleeding on probing.
4,143 citations