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A salivary metabolite signature that reflects gingival host-microbe interactions: instability predicts gingivitis susceptibility.


ABSTRACT: Several proteins and peptides in saliva were shown to stimulate gingival wound repair, but the role of salivary metabolites in this process remains unexplored. In vitro gingival re-epithelialization kinetics were determined using unstimulated saliva samples from healthy individuals collected during an experimental gingivitis study. Elastic net regression with stability selection identified a specific metabolite signature in a training dataset that was associated with the observed re-epithelialization kinetics and enabled its prediction for all saliva samples obtained in the clinical study. This signature encompassed ten metabolites, including plasmalogens, diacylglycerol and amino acid derivatives, which reflect enhanced host-microbe interactions. This association is in agreement with the positive correlation of the metabolite signature with the individual's gingival bleeding index. Remarkably, intra-individual signature-variation over time was associated with elevated risk for gingivitis development. Unravelling how these metabolites stimulate wound repair could provide novel avenues towards therapeutic approaches in patients with impaired wound healing capacity.

SUBMITTER: Fernandez-Gutierrez MM 

PROVIDER: S-EPMC7033112 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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A salivary metabolite signature that reflects gingival host-microbe interactions: instability predicts gingivitis susceptibility.

Fernandez-Gutierrez Marcela M MM   Imangaliyev Sultan S   Prodan Andrei A   Loos Bruno G BG   Keijser Bart J F BJF   Kleerebezem Michiel M  

Scientific reports 20200220 1


Several proteins and peptides in saliva were shown to stimulate gingival wound repair, but the role of salivary metabolites in this process remains unexplored. In vitro gingival re-epithelialization kinetics were determined using unstimulated saliva samples from healthy individuals collected during an experimental gingivitis study. Elastic net regression with stability selection identified a specific metabolite signature in a training dataset that was associated with the observed re-epithelializ  ...[more]

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