Biology subjects

Gibon, Y.

Publications and source records attributed to Gibon, Y..

9 recordsLinked to original sources

bioRxiv2026

Predictive metabolomics to decipher plant eco-evolutive tendencies and physiological traits

Plant ecological and evolutionary strategies are shaped by interactions between phylogenetic history and environmental constraints, resulting in leaf and stomatal traits. However, traditional trait-based and phylogenetic approaches often fail to fully explain biochemical mechanisms underlying ecological strategies, particularly for leaf and stomatal traits. Plant metabolomes integrate genetic, physiological, and environmental information and therefore represent a promising intermediate phenotype for investigating links between biochemical diversity, functional traits, and evolutionary patterns. We analysed metabolomic profiles from 74 plant species with various growth forms and ecological types. Using machine learning approaches, we explored whether metabolic variation could predict plant functional divisions, growth forms and phenological types, but also physiological traits related to drought resistance. Metabolomic data contained structured information associated with variation in plant functional traits, ecological strategies, and phylogenetic relationships. Machine learning models identified with high accuracy distinct metabolic signatures linked to differences among plant functional divisions, growth forms, phenology, and trait values. Our study demonstrates that predictive metabolomics provides a powerful and integrative framework to investigate plant ecological and evolutionary strategies. By linking biochemical diversity with plant phylogeny, and ecophysiological traits across multiple species, this approach offers new opportunities to explore the mechanistic basis of plant evolution.

plant biology↗

bioRxiv2026

Predictive metabolomics reveals leaf systemic metabolic signatures associated with floral traits in Camellia

The genus Camellia comprises more than 200 evergreen species of major economic and ornamental importance, characterised by high morphological and chemical diversity. While several species have been extensively studied for their bioactive compounds, the metabolic basis of floral trait variation across the genus remains poorly understood. In this study, a predictive metabolomics framework was applied to investigate the relationship between leaf metabolic profiles and floral traits, focusing on flower colour and floral form. Leaves from 315 individual trees, including 15 Camellia species and representing 1,160 samples, were analysed by untargeted metabolomics, generating a large-scale metabolic profiling dataset. A dedicated quality control strategy was implemented to ensure analytical stability across multiple injection series and flowering seasons. Penalised generalised linear models were used to uncover robust metabolic predictors associated with floral traits and to evaluate model performance through internal and external validation. Distinct sets of metabolites were associated with flower colour and floral form, with limited overlap between traits. Predictive performance was consistently higher for colour than for floral form, indicating more structured metabolic signatures for chromatic traits. The selected predictors spanned multiple major chemical classes, supporting a systemic organisation of the metabolome rather than reliance on single biosynthetic pathways. Consistently high predictive accuracies were obtained, reaching approximately 87% for both flower colour and floral form, and remaining clearly above the corresponding no-information rates ({approx} 43%). Together, these results demonstrate that leaf metabolomics can be used to robustly predict floral traits in Camellia and highlight the potential of predictive metabolomics as a tool for early phenotype inference, quality control and selection in long-lived ornamental species.

plant biology↗

bioRxiv2026

Branching Varies with Light Limitation Scenarios in relation with Changes in Carbon Source-Sink Dynamics.

Bud outgrowth is a major component of plant architectural plasticity and is influenced by light conditions. While the inhibitory effect of low light intensity on branching is well documented, the underlying regulators remain debated and, especially, the role of sugar availability has never been thoroughly evaluated. Here, we combined experiments with a computational approach quantifying carbon source-sink balance in single-axis rose plants to investigate how continuous and transient light limitation regulate bud outgrowth. Continuous low light reduced photosynthesis, leading to decreased sugar availability and inhibited bud outgrowth. In contrast, a transient period of low light followed by high light unexpectedly stimulated bud outgrowth, shortened the delay between outgrowth of successive buds, and produced an over-branched phenotype. This response resulted from a non-reversible reduction in the growth of apical organs appearing under low light, which lowered carbon demand and caused sugar over-accumulation after the return to high light. Manipulating carbon supply and demand through leaf masking, photosynthetic inhibition, and targeted sucrose feeding causally confirmed the central role of sugar availability in these contrasting responses. Beyond these findings, key requirements for models simulating branching plasticity were identified and this work provides a basis for predicting branching responses under fluctuating and complex light environments. HighlightBud outgrowth, a key component of plant plasticity, is regulated by light intensity through sugar availability. Continuous and transient low light have opposite effects by limiting sugar production and use, respectively.

plant biology↗

bioRxiv2023

Phylogenetically diverse wild plant species use common biochemical strategies to thrive in the Atacama Desert

The best ideotypes are under mounting pressure due to increased aridity in many parts of the world. Understanding the conserved molecular mechanisms that evolve in wild plant species adapted to harsh environments is crucial in developing new strategies for sustainable agriculture. Yet our knowledge of such mechanisms in wild species is scant, particularly in extreme environments. We performed metabolic pathway reconstruction using transcriptome information from 32 Atacama plant species and phylogenetically related plant species that do not live in Atacama (Sister species). We analyzed pathway and reaction enrichment to understand the biochemical commonalities and differences of wild Atacama plant species. To gain insights into the mechanisms that ensure plant survival, we compared expressed gene isoform numbers and gene expression patterns between the annotated biochemical reactions from 32 Atacama and Sister species. We found significant biochemical convergences in primary and secondary metabolism characterized by reactions enriched in at least 50% of the Atacama species across major plant phylogenetic lineages. Analysis of the annotation indicated potential advantages against drought, salinity, high solar irradiance, and nitrogen starvation. These findings suggest that the adaptation in the Atacama Desert may result in part from shared genetic legacies governing the expression of key metabolic pathways to face harsh environmental conditions. Enriched reactions corresponded to ubiquitous compounds common to extreme and agronomic species and were congruent with our previous metabolomic analyses in these Atacama species. Hence, genes underlying these adaptive traits offer promising candidates for improving abiotic stress resilience in crop species.

plant biology↗

bioRxiv2022

Blue light promotes ascorbate synthesis by deactivating the PAS/LOV photoreceptor that inhibits GDP-L-galactose phosphorylase

Ascorbate (vitamin C) is one of the most essential antioxidants in fresh fruits and vegetables. To get insights into the regulation of ascorbate metabolism in plants, a mutant producing ascorbate-enriched fruits was studied. The causal mutation, identified by a mapping-by-sequencing strategy, corresponded to a knock-out recessive mutation in a new class of photoreceptor named PAS/LOV protein (PLP, Solyc05g07020), which acts as a negative regulator of ascorbate biosynthesis in tomato. This trait was confirmed by CRISPR/Cas9 gene editing, and further found in all plant organs, including fruit that accumulated 2-3 times more ascorbate than in the WT. The functional characterization revealed that PLP interacted with the two isoforms of GDP-L-galactose phosphorylase (GGP), known as the controlling step of the L-galactose pathway of ascorbate synthesis. The interaction with GGP occurred in the cytoplasm and the nucleus, but was abolished when PLP was mutated. These results were confirmed by an optogenetic approach using an animal cell system, which additionally demonstrated that blue light modulated the PLP-GGP interaction. Assays performed in vitro with heterologously expressed GGP and PLP showed that PLP is a non-competitive inhibitor of GGP that is inactivated after blue light exposure. This discovery sheds light on the light-dependent regulation of ascorbate metabolism in plants.

plant biology↗

bioRxiv2021

From fruit growth to ripening in plantain: a careful balance between carbohydrate synthesis and breakdown

We investigated the fruit development in two plantain banana cultivars from two weeks after bunch emergence till twelve weeks through high-throughput proteomics, major metabolite quantification and metabolic flux analyses. We give for the first time an insight at early stages of starch synthesis and breakdown. Starch and sugar synthesis and breakdown are processes that take place simultaneously. During the first eight to ten weeks the balance between synthesis and breakdown is clearly in favour of sugar breakdown and a net starch synthesis occurs. During this period, plantain fruit accumulates up to 48% of starch. The initiation of the ripening process is accompanied with a shift in balance towards net starch breakdown. The key enzymes related to this are phosphoglucan water dikinase (PWD), phosphoglucan phosphatase, -1,6-glucosidase starch debranching enzyme (DBE), alpha glucan phosphorylase (PHS) and 4-alpha glucanotransferase disproportioning enzyme (DPE). The highest correlations with sucrose have been observed for PHS and DPE. There is also a significant correlation between the enzymes involved in ethylene biosynthesis, starch breakdown, pulp softening and ascorbate biosynthesis. The faster ending of maturation and starting of ripening in the Agbagba cultivar are linked to the key enzymes 1-aminocyclopropane-1-carboxylate oxidase and DPE. This knowledge of the mechanisms that regulate starch and sugar metabolisms during maturation and ripening is fundamental to determine the harvest moment, reduce postharvest losses and improve final product quality of breeding programs.

plant biology↗

bioRxiv2020

Metabolic profile discriminates and predicts Arabidopsis susceptibility to virus under field conditions

As obligatory parasites, plant viruses alter host cellular metabolism. There is a lack of information on the variability of virus-induced metabolic responses among genetically diverse plants in a natural context with daily changing conditions. To decipher the metabolic landscape of plant-virus interactions in a natural setting, one hundred and thirty-two and twenty-six accessions of Arabidopsis thaliana were inoculated with Turnip mosaic virus (TuMV), in two field experiments over 2 years. The accessions were phenotyped for viral accumulation, above-ground biomass, targeted and untargeted metabolic profiles. The accessions revealed quantitative response to the virus, from susceptibility to resistance. Susceptible accessions accumulate primary and secondary metabolites upon infection, at the cost of hindered growth. Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) revealed that the primary metabolites sucrose, glucose and glutamate discriminate susceptible and resistant accessions. Twenty-one metabolic signatures were found to significantly accumulate in resistant accessions whereas they maintained their growth at the same level as mock-inoculated plants without biomass penalty. Metabolic content was demonstrated to discriminate and to be highly predictive of the susceptibility of inoculated Arabidopsis. The PLS coefficient estimated in the training data set reveals, after cross-validation, a correlation of 0.61 between predicted and true viral accumulation. This study is the first to describe the metabolic landscape of plant-virus interactions in a natural setting and its predictive link to susceptibility. It reveals that, in this undomesticated species and in ecologically realistic conditions, growth and resistance are in a permanent conversation and provides new insights on plant-virus interactions.

plant biology↗

bioRxiv2018

A study of phenotypic plasticity of Saccharomyces cerevisiae in natural grape juices shed light on allelic variation under balanced selection.

The ability of a genotype to produce different phenotypes according to its surrounding environment is known as phenotypic plasticity. Within different individuals of the same species, phenotypic plasticity can vary greatly. This contrasted response is due to allelic variations and is caused by gene-by-environment interactions (GxE). Finding the genes and the cellular functions that interact with the environment is a current challenge for better understanding the genetic bases of phenotypic plasticity. In order to study the impact of natural allelic variations having a contrasted but relevant effect in a changing environment, we investigated the phenotypic response of the wine yeast Saccharomyces cerevisiae fermented in various grape juices. In this study we implemented a QTL mapping program using two independent offspring (~100 progeny) in order to investigate the molecular basis of yeast phenotypic response in a wine fermentation context. Thanks to high throughput sequencing approaches, both populations were genotyped, providing saturated genetic maps of thousands of markers. Linkage analyses allowed the detection of 78 QTLs including 21 with significant interaction with the nature of the fermented juice or fermentation conditions. Molecular dissection of a major QTL showed that the sulfite pump Ssu1p has a pleiotropic effect and impacts the phenotypic plasticity of several traits. Both alleles have positive effect according to external condition in phenotypes related to yeast fitness suggesting an example of balanced selection. All together these results pave the way for exploiting and deciphering the genetic determinism of phenotypic plasticity.

genetics↗

bioRxiv2017

Wine yeast phenomics: a standardized fermentation method for assessing quantitative traits of Saccharomyces cerevisiae strains in enological conditions.

This work describes the set up of a small scale fermentation methodology for measuring quantitative traits of hundreds of samples in an enological context. By using standardized screw cap vessels, the alcoholic fermentation kinetics of Saccharomyces cerevisiae strains were measured by following the weight loss over time. Preliminary results showed that the kinetic parameters measured are in agreement with those observed in larger scale vats. The small volume used did not impair any analysis of the strain performance. Indeed, this fermentation system was coupled with robotized enzymatic assays and 8 end-point metabolites of enological interest were measured accurately. Moreover, the vessel used offers the possibility to assay 32 volatiles compounds using a headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry approach. Data presented demonstrates that the shaking conditions significantly impacted the mean and the variance of kinetic parameters, primary metabolites, and the production of volatile compounds. This effect was likely due to an enhanced transfer of dissolved oxygen during the first hours of the alcoholic fermentation. To test the efficiency of this experimental design, the phenotypic response of 35 wine industrial starters was measured in five grape juices from the Bordeaux area. A multivariate analysis illustrated that strains were better discriminated by some grape must, than others. The technological performances as well as the phenotypic robustness of these strains was measured and discussed. The optimized methodology developed allows investigating multiple fermentation traits for numerous yeast strains and conditions and greatly contributes in achieving quantitative genetics studies as well as yeast selection programs.

microbiology↗