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Scripta Scientifica Pharmaceutica

IN SILICO PREDICTION OF METABOLISM AS A TOOL TO IDENTIFY NEW METABOLITES OF DIETARY MONOTERPENES IN RATS

Jarlei Fiamoncini, Bernard Lyam, Celine Dalle, Melanie Petera, Claudine Manach

Abstract

Dietary terpenes have not been studied enough, despite the fact that they are absorbed well and display a range of biological properties. Better knowledge about their metabolism will help understanding the health effects of plant foods, herbs and spices and may provide new biomarkers of food intake. As part of the FoodBAll project we are investigating the metabolism of terpenes, identifying metabolites and biotransformations involved in their metabolism. PhytoHub (database that compiles all known metabolites of dietary phytochemicals, including terpenes) and Nexus Meteor (in silico prediction of metabolism), were used to identify biotransformations involved in the metabolism of monoterpenoids. Twenty-two selected biotransformations were used to predict the metabolism of camphene, camphor, carvacrol, carvone, 1,4-cineole, 1,8-cineole, citral, citronellal, cuminaldehyde, p-cymene, fenchone, geraniol, limonene, linalool, menthol, myrcene, nootkatone, perillyl alcohol, pinene, pulegone, terpinen-4-ol and thymol. In parallel, Wistar rats received a chemically defined diet with or without 0.05% of the referred compounds. Before and after 5 days of the exposure to the dietary monoterpenes, urine was collected and untargeted metabolomics analysis performed using high-resolution mass spectrometry (UPLC-QToF).

On average, 10 metabolites per compound were identified in rat urine, including new and known ones. Identification of metabolites was based on monoisotopic mass and formula match, presence of adducts and specific mass losses indicative of glucuronidation and conjugation to amino acids. Validation of identification is being done using orbitrap MS/MS and hydrogen-deuterium exchange experiments.

The combination of in silico prediction and in vivo experiment allowed the identification of known and new metabolites of different dietary terpenoids. Predicted metabolites of terpenes will be added in PhytoHub to complement the database of known metabolites.

Acknowledgement: Agence Nationale de la Recherche - FoodBAll project (JPI HDHL)


Keywords

monoterpenoids, insilico prediction of metabolism, metabolism of phytochemicals




DOI: http://dx.doi.org/10.14748/ssp.v4i1.3945

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About The Authors

Jarlei Fiamoncini

Bernard Lyam

Celine Dalle

Melanie Petera

Claudine Manach

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