terclim by ICS banner
IVES 9 IVES Conference Series 9 Influence of grapevine rootstock/scion combination on rhizosphere and root endophytic microbiomes

Influence of grapevine rootstock/scion combination on rhizosphere and root endophytic microbiomes

Abstract

Soil is a reservoir of microorganisms playing important roles in biogeochemical cycles and interacting with plants whether in the rhizosphere or in the root endosphere. The composition of the microbial communities thus impacts the plant health. Rhizodeposits (such as sugar, organic and amino acids, secondary metabolites, dead root cells …) are released by the roots and influence the communities of rhizospheric microorganisms, acting as signaling compounds or carbon sources for microbes. The composition of root exudates varies depending on several factors including genotypes. As most of the cultivated grapevines worldwide are grafted plants, the aim of this study was to explore the influence of rootstock and scion genotypes on the microbial communities of the rhizosphere and the root endosphere. The work was conducted in the GreffAdapt plot (55 rootstocks x 5 scions), in which the 275 combinations have been planted into 3 blocks designed according to the soil resistivity. Samples of roots and rhizosphere of 10 scion x rootstock combinations were first collected in May among the blocks 2 and 3. The quantities of bacteria, fungi and archaea have been assessed in the rhizosphere by quantitative PCR, and by cultivable methods for bacteria and fungi. The communities of bacteria, fungi and arbuscular mycorrhizal fungi (AMF) was analyzed by Illumina sequencing of 16S rRNA gene, ITS and 28S rRNA gene, respectively. The level of mycorrhization was also evaluated using black ink coloration of newly formed roots harvested in October. The level of bacteria, fungi and archaea was dependent on rootstock and scion genotypes. A block effect was observed, suggesting that the soil characteristics strongly influenced the microorganisms from the rhizosphere and root endosphere. High-throughput sequencing of the different target genes showed different communities of bacteria, fungi and AMF associated with the scion x rootstock combinations. Finally, all the combinations were naturally mycorrhized. The root mycorrhization intensity was influenced by the rootstock genotype, but not by the scion one. Altogether, these results suggest that both rootstock and scion genotypes influence the rhizosphere and root endophytic microbiomes. It would be interesting to analyze the biochemical composition of the rhizodeposition of these genotypes for a better understanding of the processes involved in the modulation of these microbiomes. Moreover, crossing our data with the plant agronomic characteristics could provide insights into their roles on plant fitness.

DOI:

Publication date: May 31, 2022

Issue: Terclim 2022

Type: Poster

Authors

Vincent Lailheugue, Romain Darriaut, Ulysse Tuquoi, Tania Marzari, Joseph Tran, Elisa Marguerit and Virginie Lauvergeat

EGFV, Univ. Bordeaux, Bordeaux Sciences Agro, INRAE, ISVV, Villenave d’Ornon, France

Contact the author

Keywords

bacteria microbiome, fungi microbiome, archaea microbiome, arbuscular mycorrhizal fungi, rhizosphere, endorhizosphere, grapevine rootstock, grapevine scion

Tags

IVES Conference Series | Terclim 2022

Citation

Related articles…

Report on the work carried out by the zoning group of the O.I.V.

La création officielle du groupe Experts Zonage Vitivinicole à l’O.I.V., qui s’inscrit dans la Commission Viticulture, est récente. Le Professeur Mario FREGONI en assure la présidence depuis 1998, assisté du vice-président et du secrétaire général Mario FALCETTI. Ils ont été confirmés dans leurs fonctions lors des sessions de mars 2001. Actuellement, le groupe d’experts Zonage Vitivinicole de l’O.I.V. se compose de 40 délégués, représentant 18 pays membres. La mise en place de ce groupe a tout d’abord été initiée par l’Instituto Agrario de San Michele (Italie) et l’Unité de Recherches Vigne et Vin du Centre INRA d’Angers (France). Une collaboration entre les chercheurs s’est installée très tôt, dès 1987.

Grape texture characteristics are linked to one major qtl

Berry texture and berry skin mechanical properties have high agronomic importance, related to quality and marketing requirements of wine, table and raisin grapes.

Counting grape bunches using deep learning under different fruit and leaf occlusion conditions

Yield estimation is very important for the wine industry since provides useful information for vineyard and winery management. The early yield estimation of the grapevine provides information to winegrowers in making management decisions to achieve a better quantity and quality of grapes. In general, yield forecasts are based on destructive sampling of bunches and manual counting of berries per bunch and bunches per vine.

Diffuse light due to wildfire smoke enhances gas exchange of shaded leaves

The risk of wildfires is increasing as the frequency and severity of drought and heat waves continue to rise. Wildfires are associated with the combustion of plant materials and emit smoke. In the atmosphere, smoke may spread readily across large areas. Smoke is composed of solid and liquid phase particulates and gases and has been identified as a causal agent of “smoke taint” in wine. On a smoky day, the intensity of direct light decreases because these particulates scatter sunlight. Even though this effect is frequently assumed to decrease plant photosynthesis, this assumption ignores the potential changes in diffuse light and may be based on scant evidence.

New molecular evidence of wine yeast-bacteria interaction unraveled by untargeted metabolomic profiling

Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can consistently stimulate (MLF+ phenotype) or inhibit (MLF- phenotype) malolactic bacteria and the MLF process as a function of numerous winemaking practices, but the molecular evidence behind still remains a mystery. In this study, such evidence was elucidated by the direct comparison of extracellular metabolic profiles of MLF+ and MLF- yeast phenotypes. Untargeted metabolomics combining ultrahigh-resolution FT-ICR-MS analysis, powerful machine learning methods and a comprehensive wine metabolite database, discovered around 800 putative biomarkers and 2500 unknown masses involved in phenotypic distinction.