# Arbuscular mycorrhizal fungi as biomarkers of vineyard yield in Champagne

Lucile Pellan, Paola Fournier, Marc Brevot, Emilie Chancerel, Erwan

Guichoux, François Delmotte, Laurence Mercier, Corinne Vacher

► To cite this version:

Lucile Pellan, Paola Fournier, Marc Brevot, Emilie Chancerel, Erwan Guichoux, et al.. Arbuscular mycorrhizal fungi as biomarkers of vineyard yield in Champagne. Centenary of the OIV - 45th world congress of vine and wine, OIV, Oct 2024, Dijon, France. hal-05297879

HAL Id: hal-05297879

https://hal.inrae.fr/hal-05297879v1

Submitted on 5 Oct 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

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

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

CENTENARY OF THE OIV

45<sup>th</sup> WORLD CONGRESS
OF VINE AND WINE

14-18 OCTOBER 2024

FRANCE-DIJON

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

Arbuscular mycorrhizal fungi as biomarkers of
vineyard yield in Champagne.

**Lucile PELLAN**, Paola FOURNIER, Marc BREVOT, Emilie CHANCEREL, Erwan GUICHOUX, François DELMOTTE, Laurence MERCIER and Corinne VACHER.

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

RÉPUBLIQUE
FRANÇAISE

Liberté
Egalité
Fraternité

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

CENTRE DE RECHERCHE
ROBERT-JEAN
DE VOGUÉ

<figure><img src="image_8.png" /></figure>

PGT B
SEQUENCAGE | GENOTYPAGE
> Cropping systems are exposed to various perturbations

<figure><img src="image_9.png" /></figure>

These perturbations impact
crop productivity

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>
> Microbiome biodiversity drives plant growth and soil health, and could improve yield.

High microbiome diversity

<figure><img src="image_12.png" /></figure>

Beneficial properties

- Primary and secondary metabolites

- Hormones

- Biocontrol substances

- Soil-structuring substances...

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

Functional implications

- Soil structure and fertility

- Induction of stress tolerance

- Expression of plant fitness and agronomic traits

- Agricultural stability, productivity and security

- Resilience to climate and agronomic practices

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

Beneficial ecological mechanisms

<figure><img src="image_17.png" /></figure>

Redundancy

<figure><img src="image_18.png" /></figure>

Complementarity

<figure><img src="image_19.png" /></figure>

Synergy

<figure><img src="image_20.png" /></figure>
> The grapevine microbiome could be part of the solution to improve grapevine yield

<figure><img src="image_21.png" /></figure>

Plant Growth promoter
(focus AMF)

- increase soil stability

Pathogen antagonist

- enhance vine growth and nutrition

- increase tolerance to abiotic (and biotic)
  Direct antagonism: antibiosis,
  stress, parasatism, niche competition, ..

- causes the accumulation of bioactive
  indirect antagonism: induction
  of grapevine defense

Darniaut et al. Critical review of plant-microbe interactions: Keys to reduce病害 in grapevine. 2022
Trouvelot et al. Arbuscular mycorrhiza symbiosis in viticulture: a review. Agronomy for sustainable development, 2015
<figure><img src="image_22.png" /></figure>

## Our goal :

# Identification of root microbial biomarkers of vineyard yield in Champagne.

<figure><img src="image_23.png" /></figure>

## Our hypothesis :

- H1 : Microbial **diversity is higher** in vineyard with **high yield**.

- H2 : Some micro-organisms are root **biomarker** of grapevine high stable **yield**.

- H3 : Among **root biomarker**, Arbuscular Mycorrhizal Fungi (**AMF**) are over-represented.

<figure><img src="image_24.png" /></figure>
## 1. Plots selection

<figure><img src="image_25.png" /></figure>

Yield > homogeneous group mean = **High yield plot**

Yield < homogeneous group mean = **Low yield plot**

Geographically closest plots with
contrasted yield

<figure><img src="image_26.png" /></figure>
## 2. Sampling design

<figure><img src="image_27.png" /></figure>

1 composite sample / sampling area
n = 120
3. Sample processing & Metabarcoding

<figure><img src="image_28.png" /></figure>
> Yield contrasts of ten plot pairs selected for the study

<table><tr><td>Plot Pair 1 (n=38)</td><td>Plot Pair 2 (n=75)</td><td>Plot Pair 3 (n=103)</td><td>Plot Pair 4 (n=103)</td><td>Plot Pair 5 (n=26)</td></tr></table>

Plot resilience

<figure><img src="image_29.png" /></figure>

High yield plot (H)

Low yield plot (L)

Group mean

Yield

<figure><img src="image_30.png" /></figure>

Plot Pair 6 (n=24)

Plot Pair 7 (n=27)

Plot Pair 8 (n=56)

Plot Pair 9 (n=25)

Plot Pair 10 (n=79)

<figure><img src="image_31.png" /></figure>

Harvest year

<figure><img src="image_32.png" /></figure>
> Representativeness of Champagne region in ten plot pairs selected.

Results

<table><thead><tr><td>Plot Pair</td><td>Geographic area (Operator)</td><td>Grape variety x Pruning method</td><td>Rootstock</td><td>Plantation year (H/L)</td></tr></thead><tbody><tr><td>Pair 1</td><td>Le Mesnil sur Oger (VCP)</td><td>Chardonnay x Chablis</td><td>41B</td><td>1999 / 2002</td></tr><tr><td>Pair 2</td><td>Bouzy (MC)</td><td>Pinot Noir x Cordon</td><td>41B</td><td>2000 / 1984</td></tr><tr><td>Pair 3</td><td>Ay (MC)</td><td>Pinot Noir x Cordon</td><td>41B</td><td>1999 / 1985</td></tr><tr><td>Pair 4</td><td>Ay (MC)</td><td>Pinot Noir x Cordon</td><td>41B</td><td>1983 / 1997</td></tr><tr><td>Pair 5</td><td>Romont (MC)</td><td>Chardonnay x Chablis</td><td>41B</td><td>2003 / 1988</td></tr><tr><td>Pair 6</td><td>Oger (VCP)</td><td>Chardonnay x Chablis</td><td>41B</td><td>1998 / 1992</td></tr><tr><td>Pair 7</td><td>Vertus (VCP)</td><td>Chardonnay x Chablis</td><td>41B</td><td>2002 / 1988</td></tr><tr><td>Pair 8</td><td>Avize (MC)</td><td>Chardonnay x Chablis</td><td>41B</td><td>2004 / 1987</td></tr><tr><td>Pair 9</td><td>Hautvillers (MC)</td><td>Pinot Noir x Cordon</td><td>41B</td><td>1997 / 1988</td></tr><tr><td>Pair 10</td><td>Cramant (MC)</td><td>Chardonnay x Chablis</td><td>41B</td><td>2005 / 1994</td></tr></tbody></table>

<figure><img src="image_33.png" /></figure>
> Microbial composition of root microbiome

<figure><img src="image_34.png" /></figure>

Fungi

<figure><img src="image_35.png" /></figure>

Root microbiota

Bacteria

<figure><img src="image_36.png" /></figure>

<figure><img src="image_37.png" /></figure>
> Microbial diversity is not correlated with grapevine yield

<figure><img src="image_38.png" /><figcaption>Fungal diversity</figcaption></figure>

<figure><img src="image_39.png" /></figure>

<figure><img src="image_40.png" /></figure>

<figure><img src="image_41.png" /><figcaption>Bacterial diversity</figcaption></figure>

<figure><img src="image_42.png" /></figure>

Pairwise comparisons using Wilcoxon rank test
> Combining approaches to identify biomarker of grapevine yield.

Small microbial dataset is used to train the Random Forest algorithm to classify samples into groups. Then, the algorithm is used to predict the variable of interest for other samples, for which only the microbial community composition is known.

<figure><img src="image_43.png" /></figure>

Differential Abundance analysis
based on linear model

Analysis of statistical significance
of associations between species
groups and variables, based on
permutation test.

Nearing, Douglas *et al.* (2021). Microbiome differential abundance methods produce disturbingly different results across 38 datasets. *Nature Communication*, 2021

Rudar *et al.* LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data. *BMC bioinformatics*, 2022

Gobbi *et al.* A global microbiome survey of vineyard soils highlights the microbial dimension of viticultural terroirs. *Communications Biology*, 2022.
> Some fungal micro-organisms are root biomarkers of grapevine yield.

<figure><img src="image_44.png" /></figure>

A

Random
Forest
0

2

IndicSpecies
35

0

5
15

Maaslin2
1

B

<figure><img src="image_45.png" /></figure>

Biomarkers associated to High Yield plots

Biomarkers associated to Low Yield plots

<figure><img src="image_46.png" /></figure>

58 Fungal and
Oomycete Root
Biomarkers of Yield
> Biomarker of grapevine yield belong to various lifestyles & fonctions

<figure><img src="image_47.png" /></figure>

<figure><img src="image_48.png" /></figure>

58 Fungal and Oomycete
Root Biomarkers of Yield

<figure><img src="image_49.png" /></figure>
> Conclusion :

- H1 : Microbial **diversity is higher** in plots with **high yield**.

No significant relationships between **fungal diversity** and **grapevine yield**.

- H2: Some micro-organisms are root **biomarker** of grapevine **yield**.

We were able to identify **58 fungal microorganisms** (genera or species) that are positively **associated with greater grapevine yield** in root samples.

- H3 : Among **root biomarker**, Arbuscular Mycorrhizal Fungi (AMF) are over-represented

<figure><img src="image_50.png" /></figure>
> Outlooks :

- Sequencing extracted DNA using AMF-specific primers

<figure><img src="image_51.png" /></figure>

PGTB
SEQUENCAGE | GENOTYPAGE

- Re-sequence the root DNA using long-read technology to cover the entire 16S RNA sequence

- Microbial community analyses of the soil compartment as a reservoir in the same plots, combined with soil physicochemical analyses, to determine the influence of soil type on microbiota distribution and better control of confounding factors

- Assess the predictive power of these microbial biomarkers using random forest algorithms

- Develop a molecular diagnostic tool to monitor biomarker abundance
  → Microfluidic Chip

BC2GRPE
BioControl to Grape

<figure><img src="image_52.png" /></figure>

<figure><img src="image_53.png" /></figure>
> Special thanks to my collaborators ...

**UMR SAVE:** Corinne VACHER, François DELMOTTE, Paola FOURNIER, Maureen PELLAN, Jessica VALLANCE, Aarti JASWA, Marie-Cécile DUFOUR.

**Moët-Hennessy:** Laurence MERCIER, Marc BREVOT, Tatiana SVINARTCHUK et collaborateurs (Léa PAVALLIER, Julien JEANMOUGIN, Maxime EVRARD, Manon COMBE, Pierre GHEUSI, Justine DUBOST).

**UMR BIOGECO/PGTB:** Yannick MELLERIN, Erwan GUICHOUX, Emilie CHANCEREL, Zoé DELPORTE, Zachary ALLOUCHE.

**EGFV:** Virginie LAUVERGEAT, Vincent LAILHEUGUE.

**LIPME :** Margot TRINQUIER.

**UMR Agroécologie:** Pierre-Emmanuel COURTY, Daniel WIPF.

save
santé et agroécologie du vignoble

MoëtHennessy
CÔUR UNG CHATEAUX
ROBERT-JEAN
DE VOGUÉ

université
de BORDEAUX

<figure><img src="image_54.png" /></figure>

PGTB
SEQUENCAGE | GENOTYPAGE

<figure><img src="image_55.png" /></figure>

<figure><img src="image_56.png" /></figure>

ISVV
INSTITUT DES SCIENCES
DE LA VIGNE ET DU VIN
BORDEAUX AQUITAINE

<figure><img src="image_57.png" /></figure>

Agroécologie
Dijon
Unité de Recherche

<figure><img src="image_58.png" /></figure>

INRAO

Arbuscular mycorrhizal fungi as biomarkers of vineyard yield in Champagne

10.2024 / Lucile PELLAN
Thank you for your attention!

<figure><img src="image_59.png" /></figure>

Lucile PELLAN (lucile.pellan@inrae.fr)

<figure><img src="image_60.png" /></figure>