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Advancements toward a systems level understanding of the human oral microbiome
Open accessAbstract
Oral microbes represent one of the most well studied microbial communities owing to the fact that they are a fundamental part of human development influencing health and disease, an easily accessible human microbiome, a highly structured and remarkably resilient biofilm as well as a model of bacteria-bacteria and bacteria-host interactions. In the last 80 years since oral plaque was first characterized for its functionally stable physiological properties such as the highly repeatable rapid pH decrease upon carbohydrate addition and subsequent recovery phase, the fundamental approaches to study the oral microbiome have cycled back and forth between community level investigations and characterizing individual model isolates. Since that time, many individual species have been well characterized and the development of the early plaque community, which involves many cell-cell binding interactions, has been carefully described. With high throughput sequencing enabling the enormous diversity of the oral cavity to be realized, a number of new challenges to progress were revealed. The large number of uncultivated oral species, the high interpersonal variability of taxonomic carriage and the possibility of multiple pathways to dysbiosis pose as major hurdles to obtain a systems level understanding from the community to the gene level. It is now possible however to start connecting the insights gained from single species with community wide approaches. This review will discuss some of the recent insights into the oral microbiome at a fundamental level, existing knowledge gaps, as well as challenges that have surfaced and the approaches to address them.
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“Local variation in site-specific “core” microbial members speaks to the heterogeneity of influences bacterial communities experience, including host factors such as age, diet, geography and oral health[180–182].”
From Enterosalivary nitrate metabolism and the microbiome: Intersection of microbial metabolism, nitric oxide and diet in cardiac and pulmonary vascular health (2017) · cites this paper as [180]
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Metadata
- Authors
- McLean, J. S.
- Affiliations
- J. Craig Venter Institute (US)
- Corresponding author
- McLean, Jeffrey S.
- ORCID
- McLean, Jeffrey S.
- Venue
- Frontiers in Cellular and Infection Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2014-07-29
- Volume
- 4
- Pages
- 98-98
- ISSN
- 2235-2988 (ISSN-L)
- PMC
- PMC4114298
- OpenAlex
- W2040159150
- Cited by
- 108
- References
- 95
- Citations by year
- 2026: 11 · 2025: 8 · 2024: 5 · 2023: 20 · 2022: 6 · 2021: 6 · 2020: 9 · 2019: 6 · 2018: 12 · 2017: 8 · 2016: 6 · 2015: 10 · 2014: 1
- FWCI
- 11.13
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Cellular and Infection Microbiology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (5r01de020102-10)
- National Institute of Dental and Craniofacial Research (R01-DE020102)
- Topics
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bacterial biofilms and quorum sensing
- Keywords
- oral microbiota, dental plaque, biofilm, dysbiosis, interpersonal variability, host-bacteria interactions, bacterial-bacterial interactions
- MeSH terms
- Bacteria, Dental Plaque, Humans, Hydrogen-Ion Concentration, Mouth, Phylogeny, Tooth Demineralization, Bacterial Physiological Phenomena, Biofilms, Host-Pathogen Interactions, Metagenome, Metagenomics, Microbial Interactions, Microbiota, Datasets as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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