# Unravelling the phytochemical profile of pubescent oak (Quercus pubescens Willd.) for wines and spirits aging

**Baptiste Guillon**¹, **Laëtitia Fougère**¹, **Cyril Colas**¹, **Gaëlle Buche**¹, **Émilie Destandau**¹

1: Institut de Chimie Organique et Analytique (UMR 7311) – Université d'Orléans, CNRS

## Introduction

Most of wood solutions used for wines and spirits aging are made from **oak** (barrels, staves, chips), and the two species traditionally used are respectively **sessile & pedunculate oak** (*Quercus petraea* Liebl. & *Quercus robur* L.).

The oak forests of the Centre-Val de Loire region are renowned for the quality of their trees. However, with climate changes, these forests are becoming vulnerable, and other oak species, especially the **pubescent oak** (*Quercus pubescens* Willd.) **more resistant to drought**, could be subject to assisted migration to conserve the specific biodiversity of the oak grove.

We also know that properties of pubescent oak wood for staves are improving upon some populations, and we can now envisage the use of these trees in cooperage, since it is widely recognized that **the chemical composition of the wood influences the organoleptic character (astringency, aroma, sweetness) of wines.**

Accessing the phytochemical profile of pubescent oak therefore represents a major challenge for **predicting changes in the taste and olfactory qualities of wines and spirits as they age.**

<figure><img src="image_1.png" /></figure>

## Untargeted Metabolomics

### Data acquisition

with UHPLC-Q-TOF-HRMS

UHPLC : Ultimate3000 with DAD detector (Thermo Scientific)

HRMS : Q-TOF maXis ESI +/- (Bruker)

Ultrasonic-assisted heartwood extraction following Buche *et al.* (2020) protocol (H₂O/EtOH) on *Q. petraea*, *Q. robur* & *Q. pubescens* :

25 samples/species (biological replicates) + 1 QC/species for MS-MS analysis

### Data processing

<figure><img src="image_2.png" /></figure>

Buche *et al.* (2020) Untargeted UHPLC-Q-TOF-HRMS based determination of discriminating compounds for oak species *Quercus robur* L. and *Quercus petraea* Liebl. identification. Phytochem. Analysis. 1-12.

## Multivariate Analysis

<figure><img src="image_3.png" /></figure>

...but also separate each other based on a few molecules more accumulated depending on the species.

## Molecular Networks Analysis

<figure><img src="image_4.png" /></figure>

The molecular network showcases 3 main clusters where *Q. pubescent* differentially accumulates molecules, which correspond to **bartogenic acid derivatives**, **glycosyl compounds**, and a cluster that remains to be elucidated. That third cluster seems to be associated to bartogenic acid derivatives as well, **with different substitutents**, and **so, different fragmentation patterns**.

With the top40 of PLS-DA Variable Importance Projection (VIP), we could retrieve some features (RT - *m/z*) in the molecular networks and propose a putative ID (as shown on the left) : features were assigned to pseudo-molecular ions, then manually and putatively annotated with *in silico* fragmentation spectra comparison with SIRIUS, and fragments raw formulas generated with Metaboscape®. Many features have yet to be annotated.

*Buche *et al.* (2021) Oak species *Quercus robur* L. and *Quercus petraea* Liebl. Identification based on UHPLC-HRMS/MS molecular networks. Metabolites, 11, 684.

## Conclusions

* The multivariate analysis displayed a **unique phytochemical fingerprint among each species**, with a clear separation of *Q. petraea*, and more subtle difference between *Q. robur* & *Q. pubescens*.

* This is supported by the molecular network analysis where *Q. pubescens* express a molecular profile mostly shared with *Q. robur*, whereas *Q. petraea* has its own molecular fingerprint : in *Q. pubescens*, we retrieve ellagitannins common to the 3 species, bartogenic acid derivatives common to *Q. robur*, and some compounds in specific clusters seem to be more abundant (molecules with bartogenic acid aglycones) and need further investigation.

## Acknowledgements

Authors gratefully acknowledge major financial support from **Région Centre Val de Loire** on FUTUROCHÈNE project which

made this study possible.

We also thank the **SALSA platform** for chromatographic and spectrometric analysis (UHPLC-HRMS). Authors thanks the projects ChemBio SFEDER-FSE 2014-2020-EX003677), Valbiocosm (FEDER-FSE 2014-2020-EX003202), Techsab (FEDER-FSE 2014-2020-EX011313), QUALICHIM (APR-IA-PF 2021-00149467), Project ESTIM-ICOA (CPER/FEDER-FSE+ 2021-2027-00022860), the RTR Motivhealth (2019-00131403) and the Labex programs SYNORG (ANR-11-LABX-0029) and IRON (ANR-11-LABX-0018-01) for their financial support of ICOA, UMR 7311, University of Orléans, CNRS.

We'd like to thank the RFMF for providing us with a travel grant that enabled me to showcase our work during this event.