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Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data
OBJECTIVE: Microorganisms play a key role in the initiation and progression of periodontal disease. Research studies have focused on seeking specific microorganisms for diagnosing and monitoring the outcome of periodontitis treatment. Large samples may help to discover novel potential biomarkers and...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248787/ https://www.ncbi.nlm.nih.gov/pubmed/34222038 http://dx.doi.org/10.3389/fcimb.2021.663756 |
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author | Cai, Zhengwen Lin, Shulan Hu, Shoushan Zhao, Lei |
author_facet | Cai, Zhengwen Lin, Shulan Hu, Shoushan Zhao, Lei |
author_sort | Cai, Zhengwen |
collection | PubMed |
description | OBJECTIVE: Microorganisms play a key role in the initiation and progression of periodontal disease. Research studies have focused on seeking specific microorganisms for diagnosing and monitoring the outcome of periodontitis treatment. Large samples may help to discover novel potential biomarkers and capture the common characteristics among different periodontitis patients. This study examines how to screen and merge high-quality periodontitis-related sequence datasets from several similar projects to analyze and mine the potential information comprehensively. METHODS: In all, 943 subgingival samples from nine publications were included based on predetermined screening criteria. A uniform pipeline (QIIME2) was applied to clean the raw sequence datasets and merge them together. Microbial structure, biomarkers, and correlation network were explored between periodontitis and healthy individuals. The microbiota patterns at different periodontal pocket depths were described. Additionally, potential microbial functions and metabolic pathways were predicted using PICRUSt to assess the differences between health and periodontitis. RESULTS: The subgingival microbial communities and functions in subjects with periodontitis were significantly different from those in healthy subjects. Treponema, TG5, Desulfobulbus, Catonella, Bacteroides, Aggregatibacter, Peptostreptococcus, and Eikenella were periodontitis biomarkers, while Veillonella, Corynebacterium, Neisseria, Rothia, Paludibacter, Capnocytophaga, and Kingella were signature of healthy periodontium. With the variation of pocket depth from shallow to deep pocket, the proportion of Spirochaetes, Bacteroidetes, TM7, and Fusobacteria increased, whereas that of Proteobacteria and Actinobacteria decreased. Synergistic relationships were observed among different pathobionts and negative relationships were noted between periodontal pathobionts and healthy microbiota. CONCLUSION: This study shows significant differences in the oral microbial community and potential metabolic pathways between the periodontitis and healthy groups. Our integrated analysis provides potential biomarkers and directions for in-depth research. Moreover, a new method for integrating similar sequence data is shown here that can be applied to other microbial-related areas. |
format | Online Article Text |
id | pubmed-8248787 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82487872021-07-02 Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data Cai, Zhengwen Lin, Shulan Hu, Shoushan Zhao, Lei Front Cell Infect Microbiol Cellular and Infection Microbiology OBJECTIVE: Microorganisms play a key role in the initiation and progression of periodontal disease. Research studies have focused on seeking specific microorganisms for diagnosing and monitoring the outcome of periodontitis treatment. Large samples may help to discover novel potential biomarkers and capture the common characteristics among different periodontitis patients. This study examines how to screen and merge high-quality periodontitis-related sequence datasets from several similar projects to analyze and mine the potential information comprehensively. METHODS: In all, 943 subgingival samples from nine publications were included based on predetermined screening criteria. A uniform pipeline (QIIME2) was applied to clean the raw sequence datasets and merge them together. Microbial structure, biomarkers, and correlation network were explored between periodontitis and healthy individuals. The microbiota patterns at different periodontal pocket depths were described. Additionally, potential microbial functions and metabolic pathways were predicted using PICRUSt to assess the differences between health and periodontitis. RESULTS: The subgingival microbial communities and functions in subjects with periodontitis were significantly different from those in healthy subjects. Treponema, TG5, Desulfobulbus, Catonella, Bacteroides, Aggregatibacter, Peptostreptococcus, and Eikenella were periodontitis biomarkers, while Veillonella, Corynebacterium, Neisseria, Rothia, Paludibacter, Capnocytophaga, and Kingella were signature of healthy periodontium. With the variation of pocket depth from shallow to deep pocket, the proportion of Spirochaetes, Bacteroidetes, TM7, and Fusobacteria increased, whereas that of Proteobacteria and Actinobacteria decreased. Synergistic relationships were observed among different pathobionts and negative relationships were noted between periodontal pathobionts and healthy microbiota. CONCLUSION: This study shows significant differences in the oral microbial community and potential metabolic pathways between the periodontitis and healthy groups. Our integrated analysis provides potential biomarkers and directions for in-depth research. Moreover, a new method for integrating similar sequence data is shown here that can be applied to other microbial-related areas. Frontiers Media S.A. 2021-06-17 /pmc/articles/PMC8248787/ /pubmed/34222038 http://dx.doi.org/10.3389/fcimb.2021.663756 Text en Copyright © 2021 Cai, Lin, Hu and Zhao https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cellular and Infection Microbiology Cai, Zhengwen Lin, Shulan Hu, Shoushan Zhao, Lei Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data |
title | Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data |
title_full | Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data |
title_fullStr | Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data |
title_full_unstemmed | Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data |
title_short | Structure and Function of Oral Microbial Community in Periodontitis Based on Integrated Data |
title_sort | structure and function of oral microbial community in periodontitis based on integrated data |
topic | Cellular and Infection Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248787/ https://www.ncbi.nlm.nih.gov/pubmed/34222038 http://dx.doi.org/10.3389/fcimb.2021.663756 |
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