ArticleNPJ biofilms and microbiomes2024
Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis.
Article in NPJ biofilms and microbiomes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Nasopharyngeal Bacterial-Fungal Dysbiosis in Respiratory-Diseased Endangered Forest Musk Deer (Biology · 2026Article
- Advances in oral disease models: a mini-review of developments from 2015 to 2025.Frontiers in dental medicine · 2026Review
- Delayed shifts in salivary microbiota composition following long-term use of 0.06% chlorhexidine toothpaste.Frontiers in oral health · 2026Article
- Modelling of the Systemic Inflammatory Host Response in Relation to the Microbiome of the Endodontic Infection.International endodontic journal · 2025Article
- parafac4microbiome: exploratory analysis of longitudinal microbiome data using parallel factor analysis.mSystems · 2025Article
- Editorial for "Advances in Oral Diseases Diagnosis and Management: 2nd Edition".Diagnostics (Basel, Switzerland) · 2025Article
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Authors and funding
9 authors.
Funding
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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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Registered trials
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