Dataset Information

Analysis of microbiota associated with peri-implantitis using 16S rRNA gene clone library.

ABSTRACT: BACKGROUND:Peri-implantitis (PI) is an inflammatory disease which leads to the destruction of soft and hard tissues around osseointegrated implants. The subgingival microbiota appears to be responsible for peri-implant lesions and although the complexity of the microbiota has been reported in PI, the microbiota responsible for PI has not been identified. OBJECTIVE:The purpose of this study was to identify the microbiota in subjects who have PI, clinically healthy implants, and periodontitis-affected teeth using 16S rRNA gene clone library analysis to clarify the microbial differences. DESIGN:Three subjects participated in this study. The conditions around the teeth and implants were evaluated based on clinical and radiographic examinations and diseased implants, clinically healthy implants, and periodontally diseased teeth were selected. Subgingival plaque samples were taken from the deepest pockets using sterile paper points. Prevalence and identity of bacteria was analyzed using a 16S rRNA gene clone library technique. RESULTS:A total of 112 different species were identified from 335 clones sequenced. Among the 112 species, 51 (46%) were uncultivated phylotypes, of which 22 were novel phylotypes. The numbers of bacterial species identified at the sites of PI, periodontitis, and periodontally healthy implants were 77, 57, and 12, respectively. Microbiota in PI mainly included Gram-negative species and the composition was more diverse when compared to that of the healthy implant and periodontitis. The phyla Chloroflexi, Tenericutes, and Synergistetes were only detected at PI sites, as were Parvimonas micra, Peptostreptococcus stomatis, Pseudoramibacter alactolyticus, and Solobacterium moorei. Low levels of periodontopathic bacteria, such as Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans, were seen in peri-implant lesions. CONCLUSIONS:The biofilm in PI showed a more complex microbiota when compared to periodontitis and periodontally healthy teeth, and it was mainly composed of Gram-negative anaerobic bacteria. Common periodontopathic bacteria showed low prevalence, and several bacteria were identified as candidate pathogens in PI.

SUBMITTER: Koyanagi T

PROVIDER: S-EPMC3084566 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

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Analysis of microbiota associated with peri-implantitis using 16S rRNA gene clone library.

Koyanagi Tatsuro T Sakamoto Mitsuo M Takeuchi Yasuo Y Ohkuma Moriya M Izumi Yuichi Y

Journal of oral microbiology 20100524

<h4>Background</h4>Peri-implantitis (PI) is an inflammatory disease which leads to the destruction of soft and hard tissues around osseointegrated implants. The subgingival microbiota appears to be responsible for peri-implant lesions and although the complexity of the microbiota has been reported in PI, the microbiota responsible for PI has not been identified.<h4>Objective</h4>The purpose of this study was to identify the microbiota in subjects who have PI, clinically healthy implants, and per ...[more]

PMID: 21523229

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Project description:BackgroundObesity is a global epidemic in the industrialized and developing world, and many children suffer from obesity-related complications. Gut microbiota dysbiosis might have significant effect on the development of obesity. The microbiota continues to develop through childhood and thus childhood may be the prime time for microbiota interventions to realize health promotion or disease prevention. Therefore, it is crucial to understand the structure and function of pediatric gut microbiota.MethodsAccording to the inclusion criteria and exclusion criteria, twenty-three normal weight and twenty-eight obese children were recruited from Nanjing, China. Genomic DNA was extracted from fecal samples. The V4 region of the bacterial 16S rDNA was amplified by PCR, and sequencing was applied to analyze the gut microbiota diversity and composition using the Illumina HiSeq 2500 platform.ResultsThe number of operational taxonomic units (OTUs) showed a decrease in the diversity of gut microbiota with increasing body weight. The alpha diversity indices showed that the normal weight group had higher abundance and observed species than the obese group (Chao1: P < 0.001; observed species: P < 0.001; PD whole tree: P < 0.001; Shannon index: P = 0.008). Principal coordinate analysis (PCoA) and Nonmetric multidimensional scaling (NMDS) revealed significant differences in gut microbial community structure between the normal weight group and the obese group. The liner discriminant analysis (LDA) effect size (LEfSe) analysis showed that fifty-five species of bacteria were abundant in the fecal samples of the normal weight group and forty-five species of bacteria were abundant in the obese group. In regard to phyla, the gut microbiota in the obese group had lower proportions of Bacteroidetes (51.35%) compared to the normal weight group (55.48%) (P = 0.030). There was no statistical difference in Firmicutes between the two groups (P = 0.436), and the Firmicutes/Bacteroidetes between the two groups had no statistical difference (P = 0.983). At the genus level, Faecalibacterium, Phascolarctobacterium, Lachnospira, Megamonas, and Haemophilus were significantly more abundant in the obese group than in the normal weight group (P = 0.048, P = 0.018, P < 0.001, P = 0.040, and P = 0.003, respectively). The fecal microbiota of children in the obese group had lower proportions of Oscillospira and Dialister compared to the normal weight group (P = 0.002 and P = 0.002, respectively).ConclusionsOur results showed a decrease in gut microbiota abundance and diversity as the BMI increased. Variations in the bacterial community structure were associated with obesity. Gut microbiota dysbiosis might play a crucial part in the development of obesity in Chinese children.

Dataset Information

Analysis of microbiota associated with peri-implantitis using 16S rRNA gene clone library.

Publications

Analysis of microbiota associated with peri-implantitis using 16S rRNA gene clone library.

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