| Title: |
Comparative constraint-based modelling of fruit development across species highlights nitrogen metabolism in the growth- defence trade-off |
| Authors: |
Chloé, Beaumont; Cédric, Cassan; Prigent, Sylvain; Ghislaine, Hilbert-Masson; Christel, Renaud; Emilia, Dell'Aversana; Petronia, Carillo; Annick, Moing; Bertrand, Beauvoit; Tim, Mccubbin; Lars Keld, Nielsen; Yves, Gibon; Sophie, Colombié |
| Contributors: |
Biologie du fruit et pathologie (BFP); Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Plateforme Bordeaux Metabolome; Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Bordeaux; MetaboHUB-MetaboHUB; Ecophysiologie et Génomique Fonctionnelle de la Vigne (UMR EGFV); Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Università degli studi della Campania "Luigi Vanvitelli" = University of the Study of Campania Luigi Vanvitelli; The University of Queensland (UQ All campuses : Brisbane, Dutton Park Gatton, Herston, St Lucia and other locations ); Australian Institute for Bioengineering and Nanotechnology (AIBN); ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011); ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011); European Project: 952908,H2020-NMBP-TR-IND-2018-2020,H2020-NMBP-TR-IND-2020-twostage,GLOMICAVE(2020) |
| Source: |
JOBIM 2024 - Journées Ouvertes en Biologie, Informatique et Mathématiques ; https://hal.science/hal-04677435 ; JOBIM 2024 - Journées Ouvertes en Biologie, Informatique et Mathématiques, Jun 2024, Toulouse, France |
| Publisher Information: |
CCSD |
| Publication Year: |
2024 |
| Collection: |
Institut National de la Recherche Agronomique: ProdINRA |
| Subject Terms: |
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]; [SDV.BV]Life Sciences [q-bio]/Vegetal Biology |
| Subject Geographic: |
Toulouse; France |
| Description: |
International audience ; Plant genetic diversity is great within plant species. On the other hand, their development is closely linked to primary metabolism and its regulation at different levels, whether through gene expression, enzymatic activities and the abundance of metabolites. Recent work compared the growth of eight fruit species, and showed that among the major compounds of biomass, some are essential for predicting the relative growth rate of fruits (RGR). Constraint-based metabolic modelling has provided a robust framework to predict metabolic fluxes and study how the plant metabolic network generates specific profiles during fruit development. This approach was applied to the panel of eight fruit species using a metabolic model based on the knowledge of heterotrophic cells, which describes a generic metabolic network of primary metabolism. Metabolic fluxes were estimated by restricting the model with a comprehensive set of metabolites and major biomass compounds quantified throughout fruit development. Multivariate analyses revealed a clear common pattern of flux distribution during fruit development with differences between fast- and slow-growing fruits. Notably, only the latter fruits mobilize the tricarboxylic acid cycle in addition to glycolysis, leading to a higher rate of respiration. Building virtual fruits by combining 12 biomass compounds revealed that the growth-defense trade-off is primarily supported by cell wall synthesis for fast-growing fruits and total polyphenol accumulation for slow-growing fruits. Recently, transcriptomic data were generated on the same panel of fruits to compare transcriptome dynamics during fruit development. The relationships between total transcript concentration and four characteristics of fruit development: developmental progress, fruit growth, RGR and protein content were investigated. Finally, predictions of these traits from the transcriptome were obtained very satisfactorily with a machine learning model, highlighting the key role of protein synthesis. |
| Document Type: |
conference object |
| Language: |
English |
| Relation: |
info:eu-repo/grantAgreement//952908/EU/Global Omic Data Integration on Animal, Vegetal and Environment Sectors/GLOMICAVE |
| Availability: |
https://hal.science/hal-04677435 |
| Accession Number: |
edsbas.A9D3FADF |
| Database: |
BASE |