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Cited by 115Oral microbiology and periodontitis researchMicrobial Community Ecology and PhysiologyGut microbiota and health

The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.

A spatial gradient of bacterial diversity in the human oral cavity shaped by salivary flow

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Proctor, Diana M., Fukuyama, Julia A., Loomer, Peter M., Armitage, Gary C., Lee, Stacey A., Davis, Nicole M., Ryder, Mark I., Holmes, Susan P., Relman, David A.·2018·Nature Communications
DOI 10.1038/s41467-018-02900-1PMC PMC5813034
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Abstract

Spatial and temporal patterns in microbial communities provide insights into the forces that shape them, their functions and roles in health and disease. Here, we used spatial and ecological statistics to analyze the role that saliva plays in structuring bacterial communities of the human mouth using >9000 dental and mucosal samples. We show that regardless of tissue type (teeth, alveolar mucosa, keratinized gingiva, or buccal mucosa), surface-associated bacterial communities vary along an ecological gradient from the front to the back of the mouth, and that on exposed tooth surfaces, the gradient is pronounced on lingual compared to buccal surfaces. Furthermore, our data suggest that this gradient is attenuated in individuals with low salivary flow due to Sjögren’s syndrome. Taken together, our findings imply that salivary flow influences the spatial organization of microbial communities and that biogeographical patterns may be useful for understanding host physiological processes and for predicting disease.

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Fig. 1 Subject, tooth class, and tooth aspect explain variation in oral communities. Adonis and PCoA on Bray Curtis dissimilarity (90 taxa, 3393 samples) revealed separation of communities by a subject, b tooth class, and c tooth aspect. d Each boxplot box demarcates the first and third quartiles of the PCoA axis 1 scores, while the horizontal black lines within each box define the median PCoA axis 1 scores. Boxes are colored according to tooth class (incisor, molar). Boxplots comparing buccal molar communities (N = 849) to those on the buccal incisors (N = 849), lingual molars (N = 846), and lingual incisors (N = 849) revealed an interaction between tooth class and tooth aspect, highlighting the greater separation of molar and incisor communities at the lingual, as compared to the buccal, tooth aspect
Fig. 1 Subject, tooth class, and tooth aspect explain variation in oral communities. Adonis and PCoA on Bray Curtis dissimilarity (90 taxa, 3393 samples) revealed separation of communities by a subject, b tooth class, and c tooth aspect. d Each boxplot box demarcates the first and third quartiles of the PCoA axis 1 scores, while the horizontal black lines within each box define the median PCoA axis 1 scores. Boxes are colored according to tooth class (incisor, molar). Boxplots comparing buccal molar communities (N = 849) to those on the buccal incisors (N = 849), lingual molars (N = 846), and lingual incisors (N = 849) revealed an interaction between tooth class and tooth aspect, highlighting the greater separation of molar and incisor communities at the lingual, as compared to the buccal, tooth aspectCC BY · PubMed Central
Fig. 2 Supragingival communities vary by tooth class in a structured fashion suggestive of a gradient. a Trend surface analysis (TSA) was performed on the species by sample data matrix (117 taxa, 1701 samples). TSA axis 1 scores (y axis) are plotted as a function of universal tooth number (x axis). Each box demarcates the first and third quartiles of the TSA axis 1 scores, for each tooth, while the horizontal black lines within each box define the median TSA axis 1 scores. Boxes are colored according to tooth class (molars, incisors, other tooth classes) and samples from the lingual and buccal tooth aspects are shown separately. Molar communities (lingual N = 248; buccal N = 249) appeared to be associated with more positive scores along axis 1 compared to incisor communities (lingual N = 250, buccal N = 249) that shared more negative axis 1 scores. Of special interest, canine (lingual N = 125; buccal N = 126) and premolar (lingual N = 227; buccal N = 227) communities appeared to be arrayed in an ordered fashion in between the molar and incisor poles. b The between-taxa correlation matrix arranged by hierarchical clustering with average linkage revealed groups of taxa that shared positive or negative correlations in their distributions across samples and c exhibited a significant pattern of spatial dependence in their distributions across sites (Moran’s I, adj. p < 0.05)
Fig. 2 Supragingival communities vary by tooth class in a structured fashion suggestive of a gradient. a Trend surface analysis (TSA) was performed on the species by sample data matrix (117 taxa, 1701 samples). TSA axis 1 scores (y axis) are plotted as a function of universal tooth number (x axis). Each box demarcates the first and third quartiles of the TSA axis 1 scores, for each tooth, while the horizontal black lines within each box define the median TSA axis 1 scores. Boxes are colored according to tooth class (molars, incisors, other tooth classes) and samples from the lingual and buccal tooth aspects are shown separately. Molar communities (lingual N = 248; buccal N = 249) appeared to be associated with more positive scores along axis 1 compared to incisor communities (lingual N = 250, buccal N = 249) that shared more negative axis 1 scores. Of special interest, canine (lingual N = 125; buccal N = 126) and premolar (lingual N = 227; buccal N = 227) communities appeared to be arrayed in an ordered fashion in between the molar and incisor poles. b The between-taxa correlation matrix arranged by hierarchical clustering with average linkage revealed groups of taxa that shared positive or negative correlations in their distributions across samples and c exhibited a significant pattern of spatial dependence in their distributions across sites (Moran’s I, adj. p < 0.05)CC BY · PubMed Central
Fig. 3 Mucosal communities also vary along an anterior to posterior gradient. A trend surface analysis (TSA) on samples of the oral mucosa and supragingival surfaces of 3 additional individuals (101 taxa, 542 samples) captured 10.5% of the total variation in the data, with the first axis accounting for 49% of the explained variance. TSA Axis 1 scores (y axis) are plotted as a function of tooth number (x axis). Each panel represents a unique tooth aspect (buccal, lingual) and intra-oral habitat (alveolar mucosa, keratinized gingiva, supragingival plaque, or buccal mucosa). Each point corresponds to a community sample, and samples are colored according to tooth class (molar, incisor, other tooth class). Blue curves denote local regression (loess) fits with associated 95% confidence intervals shaded in gray. Molar communities tended toward more positive scores along axis 1 compared to incisor communities, which tended toward more negative scores along axis 1 compared to molars. The remaining tooth classes were structured in an ordered fashion between the molar and incisor poles. These data suggest that both supragingival and soft tissue communities vary along a gradient from the front to the back of the mouth
Fig. 3 Mucosal communities also vary along an anterior to posterior gradient. A trend surface analysis (TSA) on samples of the oral mucosa and supragingival surfaces of 3 additional individuals (101 taxa, 542 samples) captured 10.5% of the total variation in the data, with the first axis accounting for 49% of the explained variance. TSA Axis 1 scores (y axis) are plotted as a function of tooth number (x axis). Each panel represents a unique tooth aspect (buccal, lingual) and intra-oral habitat (alveolar mucosa, keratinized gingiva, supragingival plaque, or buccal mucosa). Each point corresponds to a community sample, and samples are colored according to tooth class (molar, incisor, other tooth class). Blue curves denote local regression (loess) fits with associated 95% confidence intervals shaded in gray. Molar communities tended toward more positive scores along axis 1 compared to incisor communities, which tended toward more negative scores along axis 1 compared to molars. The remaining tooth classes were structured in an ordered fashion between the molar and incisor poles. These data suggest that both supragingival and soft tissue communities vary along a gradient from the front to the back of the mouthCC BY · PubMed Central
Fig. 4 Low salivary flow impacts the composition of microbial communities independent of past dental caries. Constrained correspondence analysis (CCA) was performed on the species × sample data matrix for the validation data set (147 taxa; 825 samples). Each point corresponds to a community sample colored by a health status (Sjögren’s, Control), b unstimulated whole-salivary flow rate (UWS-FR: 0.2, 0.4, or 0.6 mL/min), c stimulated whole-salivary flow rate (SWS-FR: 2.5, 5.0, or 7.5 ml/min), or d the index of missing, filled surfaces for smooth surface sites (MFS: 0, 1). The clustering of samples suggested that UWS-FR b and SWS-FR c explain more of the variation in the data than health status a or MFS d. To examine this explicitly, e CCA1 scores were plotted against UWS-FR, and community samples were colored according to health status of the host (Sjögren’s, Control). Samples from the one Sjögren’s patient who had a relatively high UWS-FR (~0.5 ml/min) grouped along CCA1 with control samples rather than with the other Sjögren’s samples. Likewise, f samples from the healthy control patient who had a relatively low SWS-FR (~2.5 ml/min) grouped along CCA1 with Sjögren’s samples rather than with other control samples
Fig. 4 Low salivary flow impacts the composition of microbial communities independent of past dental caries. Constrained correspondence analysis (CCA) was performed on the species × sample data matrix for the validation data set (147 taxa; 825 samples). Each point corresponds to a community sample colored by a health status (Sjögren’s, Control), b unstimulated whole-salivary flow rate (UWS-FR: 0.2, 0.4, or 0.6 mL/min), c stimulated whole-salivary flow rate (SWS-FR: 2.5, 5.0, or 7.5 ml/min), or d the index of missing, filled surfaces for smooth surface sites (MFS: 0, 1). The clustering of samples suggested that UWS-FR b and SWS-FR c explain more of the variation in the data than health status a or MFS d. To examine this explicitly, e CCA1 scores were plotted against UWS-FR, and community samples were colored according to health status of the host (Sjögren’s, Control). Samples from the one Sjögren’s patient who had a relatively high UWS-FR (~0.5 ml/min) grouped along CCA1 with control samples rather than with the other Sjögren’s samples. Likewise, f samples from the healthy control patient who had a relatively low SWS-FR (~2.5 ml/min) grouped along CCA1 with Sjögren’s samples rather than with other control samplesCC BY · PubMed Central
Fig. 5 Low salivary flow is associated with gradient modulation. A trend surface analysis was performed on supragingival samples collected from 10 low-flow subjects with Sjögren’s and 7 healthy controls. Each panel encompasses samples collected from an individual subject (control 1–7; Sjögren’s 1–10). The color of the local (loess) regression lines corresponds to the UWS-FR (low flow, moderate flow, high flow) for that subject while the gray shading encompasses the 95% confidence interval surrounding each model fit. Each point is a community sample, and shapes map to the presence (1) or absence (0) of past caries experience at each smooth surface. The gradient appears to be attenuated or modulated in most of the low-flow cohort (Sjögren’s) compared to otherwise healthy individuals (controls)
Fig. 5 Low salivary flow is associated with gradient modulation. A trend surface analysis was performed on supragingival samples collected from 10 low-flow subjects with Sjögren’s and 7 healthy controls. Each panel encompasses samples collected from an individual subject (control 1–7; Sjögren’s 1–10). The color of the local (loess) regression lines corresponds to the UWS-FR (low flow, moderate flow, high flow) for that subject while the gray shading encompasses the 95% confidence interval surrounding each model fit. Each point is a community sample, and shapes map to the presence (1) or absence (0) of past caries experience at each smooth surface. The gradient appears to be attenuated or modulated in most of the low-flow cohort (Sjögren’s) compared to otherwise healthy individuals (controls)CC BY · PubMed Central

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Metadata

Authors
Proctor, D. M., Fukuyama, J. A., Loomer, P. M., Armitage, G. C., Lee, S. A., Davis, N. M., Ryder, M. I., Holmes, S. P., & Relman, D. A.
Affiliations
  • University of California, San Francisco (US)
  • Fred Hutch Cancer Center (US)
  • Stanford Medicine (US)
  • Stanford University (US)
  • VA Palo Alto Health Care System (US)
Corresponding author
Relman, David A.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2018-02-14
Volume
9
Issue
1
Pages
681-681
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-018-02900-1
PMC
PMC5813034
OpenAlex
W2801640552
Cited by
115
References
62
Citations by year
2026: 8 · 2025: 13 · 2024: 8 · 2023: 10 · 2022: 12 · 2021: 24 · 2020: 23 · 2019: 11 · 2018: 6
FWCI
18.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • eScholarship (California Digital Library) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
  • IUScholarWorks Open (Indiana University) (submittedVersion)
Funders
  • National Institutes of Health (DP1OD000964)
  • National Institute of General Medical Sciences (T32GM007276)
  • National Institute of Allergy and Infectious Diseases (T32AI007328)
  • National Institute of Dental and Craniofacial Research (R01DE023113)
  • Division of Graduate Education
Topics
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
  • Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
Keywords
oral microbiota, salivary flow, spatial gradients, bacterial diversity, Sjögren's syndrome, dental plaque, oral mucosa, biogeography, microbial community structure, tooth surface
MeSH terms
Adult, Aged, Bacteria, Female, Humans, Male, Middle Aged, Mouth, Mouth Mucosa, RNA, Ribosomal, 16S, Saliva, Salivation, Sjogren's Syndrome, Tongue, Tooth, Genetic Variation, Xerostomia, Biodiversity, Young Adult

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