Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
[Preprint]. 2024 Aug 10:rs.3.rs-4720457.
doi: 10.21203/rs.3.rs-4720457/v1.

HIV Infection and Exposure Increases Cariogenic Taxa, Reduces Taxonomic Turnover, and Homogenizes Spatial Differentiation for the Supragingival Microbiome

Allison E Mann  1 , Ciara Aumend  2 , Suzanne Crull  2 , Lauren M O'Connell  2 , Esosa Osagie  3 , Paul Akhigbe  3 , Ozoemene Obuekwe  4 , Augustine Omoigberale  4 , Matthew Rowe  2 , Thomas Blouin  2 , Ashlyn Soule  2 , Colton Kelly  2 , Robert A Burne  5 , Modupe O Coker  6 , Vincent P Richards  2
Affiliations

HIV Infection and Exposure Increases Cariogenic Taxa, Reduces Taxonomic Turnover, and Homogenizes Spatial Differentiation for the Supragingival Microbiome

Allison E Mann et al. Res Sq. .

Update in

Abstract

Background: The oral microbiome comprises distinct microbial communities that colonize diverse ecological niches across the oral cavity, the composition of which are influenced by nutrient and substrate availability, host genetics, diet, behavior, age, and other diverse host and environmental factors. Unlike other densely populated human-associated microbial ecosystems (e.g., gut, urogenital), the oral microbiome is regularly and directly exposed to the external environment and is therefore likely less stable over time. Cross sectional studies of the oral microbiome capture a glimpse of this temporal dynamism, yet a full appreciation of the relative stability, robusticity, and spatial structure of the oral environment is necessary to understand the role of microbial communities in promoting health or disease.

Results: Here we investigate the spatial and temporal stability of the oral microbiome over three sampling time points in the context of HIV infection and exposure. Individual teeth were sampled from a cohort of 565 Nigerian children with varying levels of tooth decay severity (i.e., caries disease). We collected 1,960 supragingival plaque samples and characterized the oral microbiome using a metataxonomic approach targeting an approximately 478 bp region of the bacterial rpoC gene. We found that both infection and exposure to HIV have significant effects on the stability of the supragingival plaque microbiome at both the spatial and temporal scale. Specifically, we detect (1) significantly lower taxonomic turnover of the oral community among exposed and infected children compared to unexposed children, (2) we find that HIV infection homogenizes the oral community across the anterior and posterior dentition, and (3) that impaired immunity (i.e., low CD4 count) and low taxonomic turnover over time in children living with HIV is associated with higher frequency of cariogenic taxa including Streptococcus mutans.

Conclusions: Our results document substantial community fluctuations over time in children unexposed to HIV independent of oral health status. This suggests that the oral community, under typical conditions, rapidly adapts to environmental perturbations to maintain homeostasis and that long-term taxonomic rigidity is a signal of community dysfunction, potentially leading to a higher incidence of oral disease including caries.

Keywords: CD4 count; HIV; caries disease; longitudinal analysis; oral microbiome.

PubMed Disclaimer

Conflict of interest statement

Competing interests The authors declare that they have no competing interests Additional Declarations: No competing interests reported.

Figures

Figure 1
Figure 1. Taxonomic turnover on individual teeth is higher in HUU as compared to HEU and HI children.
(a) Principal coordinate plot of individual teeth collected from visit one and visit three for each of the three HIV status groups. Lines connect plaque samples collected from the same tooth and same individual. Point shape indicates tooth health at the time of sampling. (b) Distribution of volatility scores for each of the three groups at visit one versus visit three. (c) Predictions plot of the microbial signature model generated using all teeth with more than one sampling point (visit one, two, and three). Correlation coefficient and p value calculated from all samples in the plot independent of HIV status. (d) The top three weighted taxa in the microbial signature model for high or low volatility for HI children (purple) and HUU children (blue). There were no significant taxa detected for HEU children.
Figure 2
Figure 2. High modularity of core association networks (CAN) associated with early and late-stage caries disease.
(a) Global CAN generated by comparing all samples across all three visits. We identified six clusters of co-associated taxa with variable predicted functional outcomes. Cluster six includes taxa commonly associated with caries disease (red). Clusters defined by this global CAN network are used to color code HIV status group and individual tooth health networks (b & c). (b). CAN networks by individual tooth health. Healthy teeth (H) have a substantially more interconnected network with low modularity (Q). Both teeth with enamel lesions (E) and dentin cavities (D) have extremely sparse and poorly connected networks with high modularity. (c) CAN networks across all three visits grouped by HIV status. Modularity of each network denoted for each CAN network (Q). Polygons grouping clusters on each network are specific to that HIV status group CAN network. Colors represent cluster identity from global CAN (a). White nodes are nodes unique to that CAN.
Figure 3
Figure 3. Taxa indicative of the community composition before and after high S. mutans relative abundance on a single tooth.
Bee plots illustrate the importance of specific taxa in our random forest classification model to identify either (a) teeth before the proliferation of S. mutans or (b) teeth after the proliferation of S. mutans. SHAP value (SHapley Additive exPlanations) indicates the degree of importance for each variable on the model. Positive SHAP values indicate that that bacterial species is important for identifying the sample as belonging to the group in question while negative SHAP values indicate that the species is more important for the opposite group (i.e., before or after S. mutans). A SHAP value of zero indicates no impact on the model. For example, the red box in subpanel a is highlighting a subset of samples for which Streptococcus sanguinis is highly predictive of the sample being before the proliferation of S. mutans. Only the top ten taxa for either before or after high S. mutans relative abundance are shown. Color of points indicate how the feature value for that individual compared to the average for the entire population in which high feature value is indicated by lighter colored points. Bolded species names indicate species found in both Shapley plots.
Figure 4
Figure 4. Community stratification of the anterior and posterior dentition is clear among HUU and HEU children but is dismantled in HI children.
(a) Microbial signature of the anterior and posterior teeth among all individuals independent of HIV status. The relative weight of each taxon is listed as its coefficient value (y axis). (b) Prediction box and density plots of the microbial signature model for anterior and posterior teeth driven by the balance of taxa listed in subplot a. (c) Capscale plot depicting the Aitchison distance of anterior and posterior teeth in HUU, HEU, and HI children. Significance between groups determined by PERMANOVA analysis and listed as Bonferroni adjusted p values. Only adult H-CF teeth were included in this analysis.
See this image and copyright information in PMC

References

    1. Mager DL, Ximenez-Fyvie LA, Haffajee AD, Socransky SS. Distribution of selected bacterial species on intraoral surfaces. J Clin Periodontol. 2003;30:644–54. - PubMed
    1. Mark Welch JL, Ramírez-Puebla ST, Borisy GG. Oral Microbiome Geography: Micron-Scale Habitat and Niche. Cell Host Microbe. 2020;28:160–8. - PMC - PubMed
    1. Morillo-Lopez V, Sjaarda A, Islam I, Borisy GG, Mark Welch JL. Corncob structures in dental plaque reveal microhabitat taxon specificity. Microbiome. 2022;10:145. - PMC - PubMed
    1. Ximénez-Fyvie LA, Haffajee AD, Socransky SS. Comparison of the microbiota of supra- and subgingival plaque in health and periodontitis. J Clin Periodontol. 2000;27:648–57. - PubMed
    1. Demmitt BA, Corley RP, Huibregtse BM, Keller MC, Hewitt JK, McQueen MB, et al. Genetic influences on the human oral microbiome. BMC Genomics. 2017;18:659. - PMC - PubMed

Publication types

LinkOut - more resources