Title |
Clustering of Subgingival Microbiota Reveals Microbial Disease Ecotypes Associated with Clinical Stages of Periodontitis in a Cross-Sectional Study
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Published in |
Frontiers in Microbiology, March 2017
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DOI | 10.3389/fmicb.2017.00340 |
Pubmed ID | |
Authors |
Sébastien Boutin, Daniel Hagenfeld, Heiko Zimmermann, Nihad El Sayed, Tanja Höpker, Halina K. Greiser, Heiko Becher, Ti-Sun Kim, Alexander H. Dalpke |
Abstract |
Periodontitis is characterized by chronic inflammation associated with alteration of the oral microbiota. In contrast to previous microbiome studies focusing a priori on comparison between extreme phenotypes, our study analyzed a random sample of 85 people. The aim of this study was to link microbial differences to disease's prevalence and severity. Using next generation sequencing of 16S rRNA amplicons and cluster analysis, we observed that the population can be divided into two major ecotypes: One mainly contained periodontal healthy/mild periodontitis individuals whereas the second ecotype showed a heterogeneous microbial distribution and clustered into three distinct sub-ecotypes. Those sub-ecotypes differed with respect to the frequency of diseased patients and displayed a gradual change in distinct subgingival microbiota that goes along with clinical disease symptoms. In ecotype 2, the subgroup with no clinical signs of disease was linked to an increase of F. nucleatum vincentii but also several other species, while only in "end-stage" dysbiosis classical red complex bacteria gained overweight. Therefore, the microbial disease ecotypes observed in our population can lead to an establishment of an early microbial risk profile for clinically healthy patients. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Australia | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
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United States | 1 | 1% |
Unknown | 84 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 15 | 18% |
Student > Ph. D. Student | 10 | 12% |
Student > Master | 8 | 9% |
Student > Bachelor | 8 | 9% |
Student > Doctoral Student | 6 | 7% |
Other | 17 | 20% |
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Immunology and Microbiology | 7 | 8% |
Nursing and Health Professions | 2 | 2% |
Other | 10 | 12% |
Unknown | 26 | 31% |