Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis

G R van der Ploeg; B W Brandt; B J F Keijser; M H van der Veen; C M C Volgenant; E Zaura; A K Smilde; J A Westerhuis; A Heintz-Buschart

doi:10.1038/s41522-024-00565-x

Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis

G R van der Ploeg
, B W Brandt
, B J F Keijser
, M H van der Veen
, C M C Volgenant
, E Zaura
, A K Smilde
, J A Westerhuis
, A Heintz-Buschart

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Gingivitis-the inflammation of the gums-is a reversible stage of periodontal disease. It is caused by dental plaque formation due to poor oral hygiene. However, gingivitis susceptibility involves a complex set of interactions between the oral microbiome, oral metabolome and the host. In this study, we investigated the dynamics of the oral microbiome and its interactions with the salivary metabolome during experimental gingivitis in a cohort of 41 systemically healthy participants. We use Parallel Factor Analysis (PARAFAC), which is a multi-way generalization of Principal Component Analysis (PCA) that can model the variability in the response due to subjects, variables and time. Using the modelled responses, we identified microbial subcommunities with similar dynamics that connect to the magnitude of the gingivitis response. By performing high level integration of the predicted metabolic functions of the microbiome and salivary metabolome, we identified pathways of interest that describe the changing proportions of Gram-positive and Gram-negative microbiota, variation in anaerobic bacteria, biofilm formation and virulence.

Original language	English
Article number	89
Pages (from-to)	1-12
Number of pages	12
Journal	npj Biofilms and Microbiomes
Volume	10
Early online date	19 Sept 2024
DOIs	https://doi.org/10.1038/s41522-024-00565-x
Publication status	Published - 2024

Bibliographical note

Funding

We want to thank Michelle van der Wurff (TNO) and Tim van den Broek (TNO) for their help in data acquisition, processing and storing and Jesse Alderliesten (UU/UvA), Fred White (UvA), Cynthia Albracht (UvA), Juan Pablo Bascur (CWTS) and Rianne Warmerdam (Aiden) for their useful discussions and suggestions. The authors thank N.A.M. Rosema for coordinating the clinical study. For assistance in capturing fluorescence photographs, the authors thank Y. Altinda\u011F. For the clinical examinations the authors thank J.M. Voll (clinical plaque assessment with Silness & L\u00F6e), and S. Bizzarro (assessment of the bleeding on marginal probing). This research is supported by the Dutch Technology Foundation STW (project number 10948) and the Top Institute Food and Nutrition (TIFN), a public-private partnership on precompetitive research in food and nutrition. Organizations supporting this project had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. QLF data was obtained with funding from NWO (ZonMw-STW-NIG-program): \u201CProject 10948: Seeing is believing? A novel tool for the visualization of oral disease manifestations.\u201D GRvdP was funded by a grant from the University of Amsterdam, Research Priority Area on Personal Microbiome Health.

Funders	Funder number
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
UU/UvA
Tim van den Broek
Top Institute Food and Nutrition
ZonMw-STW-NIG-program
Universiteit van Amsterdam
Stichting voor de Technische Wetenschappen	10948

Keywords

Humans
Gingivitis/microbiology
Microbiota
Saliva/microbiology
Host Microbial Interactions
Metabolome
Biofilms/growth & development
Female
Adult
Male
Bacteria/classification
Principal Component Analysis
Mouth/microbiology
Young Adult
Healthy Volunteers

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10.1038/s41522-024-00565-x

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Cite this

van der Ploeg, G. R., Brandt, B. W., Keijser, B. J. F., van der Veen, M. H., Volgenant, C. M. C., Zaura, E., Smilde, A. K., Westerhuis, J. A., & Heintz-Buschart, A. (2024). Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis. npj Biofilms and Microbiomes, 10, 1-12. Article 89. https://doi.org/10.1038/s41522-024-00565-x

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abstract = "Gingivitis-the inflammation of the gums-is a reversible stage of periodontal disease. It is caused by dental plaque formation due to poor oral hygiene. However, gingivitis susceptibility involves a complex set of interactions between the oral microbiome, oral metabolome and the host. In this study, we investigated the dynamics of the oral microbiome and its interactions with the salivary metabolome during experimental gingivitis in a cohort of 41 systemically healthy participants. We use Parallel Factor Analysis (PARAFAC), which is a multi-way generalization of Principal Component Analysis (PCA) that can model the variability in the response due to subjects, variables and time. Using the modelled responses, we identified microbial subcommunities with similar dynamics that connect to the magnitude of the gingivitis response. By performing high level integration of the predicted metabolic functions of the microbiome and salivary metabolome, we identified pathways of interest that describe the changing proportions of Gram-positive and Gram-negative microbiota, variation in anaerobic bacteria, biofilm formation and virulence.",

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AU - Volgenant, C M C

AU - Zaura, E

AU - Smilde, A K

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AB - Gingivitis-the inflammation of the gums-is a reversible stage of periodontal disease. It is caused by dental plaque formation due to poor oral hygiene. However, gingivitis susceptibility involves a complex set of interactions between the oral microbiome, oral metabolome and the host. In this study, we investigated the dynamics of the oral microbiome and its interactions with the salivary metabolome during experimental gingivitis in a cohort of 41 systemically healthy participants. We use Parallel Factor Analysis (PARAFAC), which is a multi-way generalization of Principal Component Analysis (PCA) that can model the variability in the response due to subjects, variables and time. Using the modelled responses, we identified microbial subcommunities with similar dynamics that connect to the magnitude of the gingivitis response. By performing high level integration of the predicted metabolic functions of the microbiome and salivary metabolome, we identified pathways of interest that describe the changing proportions of Gram-positive and Gram-negative microbiota, variation in anaerobic bacteria, biofilm formation and virulence.

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KW - Male

KW - Bacteria/classification

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Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis

Abstract

Bibliographical note

Funding

Keywords

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Persistent URL (handle)

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