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The bZIP transcription factor (TF) SlTGA2.2 was previously highlighted as a possible hub in a network regulating fruit growth and transition to ripening (maturation phase). It belongs to a clade of TFs well known for their involvement in the regulation of the salicylic acid–dependent systemic acquired resistance. To investigate if this TGA TF plays a role in tomato fruit growth and maturation, we took advantage of the fruit-specific SlPPC2 promoter (PPC2pro) to target the expression of a SlTGA2.2-SRDX chimeric repressor in a developmental window restricted to early fruit growth and maturation. Here, we show that this SlTGA2.2-SRDX repressor alters early fruit development and metabolism, including chloroplast number and structure, considerably extends the time necessary to reach the mature green stage and slows down fruit ripening. RNA sequencing and plant hormone analyses reveal that PPC2pro:SlTGA2.2-SRDX fruits are maintained in an immature stage as long as PPC2pro is active, through early modifications of plant hormonal signaling and down-regulation of MADS-RIN and NAC-NOR ripening regulators. Once PPC2pro becomes inactive and therefore SlTGA2.2-SRDX expression is reduced, ripening can proceed, albeit at a slower pace than normal. Altogether, this work emphasizes the developmental continuum between fruit growth, maturation and ripening and provides a useful tool to alter and study the molecular bases of tomato fruit transition to ripening.

International audience; Besides structural information, magnetic resonance imaging (MRI) is crucial to reveal the presence and gradients of metabolites in organs constituted of several tissues. In plant science, such knowledge is key to better understand fruit development and metabolism. Routine methods based on fixation for cytological studies or dissection for metabolite measurements induce biases and plant sample destruction. Magnetic resonance spectroscopy imaging (MSRI) leads to one NMR spectrum per pixel while chemical exchange saturation transfer (CEST) MRI allows mapping metabolites having exchangeable protons. As both methods present different advantages and drawbacks, we compared them to map metabolites in ripe tomato fruits. We demonstrated that MRSI was difficult to interpret due to large spatial chemical shift variations while CEST MRI produced promising image mapping of the main carbohydrates and amino acids. It showed that glucose/fructose was mostly located in the locular tissue, whereas glutamate/glutamine/GABA was found inside the columella.Graphical abstract.

Brassinosteroids (BRs) are steroid hormones that play key roles in plant development and defense. Our goal is to harness the extensive knowledge of the Arabidopsis BR signaling network to improve productivity in crop species. This first requires identifying components of the conserved network and their function in the target species. Here, we investigated the function of SlBIM1a, the closest tomato homolog of AtBIM1, which is highly expressed in fruit. SlBIM1a-overexpressing lines displayed severe plant and fruit dwarfism, and histological characterization of different transgenic lines revealed that SlBIM1a expression negatively correlated with fruit pericarp cell size, resulting in fruit size modifications. These growth phenotypes were in contrast to those found in Arabidopsis, and this was confirmed by the reciprocal ectopic expression of SlBIM1a/b in Arabidopsis and of AtBIM1 in tomato. These results determined that BIM1 function depends more on the recipient species than on its primary sequence. Yeast two-hybrid interaction studies and transcriptomic analyses of SlBIM1a-overexpressing fruit further suggested that SlBIM1a acts through its interaction with SlBZH1 to govern the transcriptional regulation of growth-related BR target genes. Together, these results suggest that SlBIM1a is a negative regulator of pericarp cell expansion, possibly at the crossroads with auxin and light signaling.

International audience; ABSTRACT Background Processed meat intake is associated with a higher risk of colorectal and stomach cancers, coronary artery disease, and type 2 diabetes and with higher mortality, but the estimation of intake of different processed meat products in this heterogeneous food group in epidemiological studies remains challenging. Objective This work aimed at identifying novel biomarkers for processed meat intake using metabolomics. Methods An untargeted, multi-tiered metabolomics approach based on LC-MS was applied to 33 meat products digested in vitro and secondly to urine and plasma samples from a randomized crossover dietary intervention in which 12 volunteers consumed successively 3 processed meat products (bacon, salami, and hot dog) and 2 other foods used as controls, over 3 consecutive days. The putative biomarkers were then measured in urine from 474 subjects from the European Prospective Investigation into Cancer and Nutrition (EPIC) cross-sectional study for which detailed 24-h dietary recalls and FFQs were available. Results Syringol and 4 derivatives of syringol were found to be characteristic of in vitro digests of smoked meat products. The same compounds present as sulfate esters in urine increased at 2 and 12 h after consumption of smoked meat products (hot dog, bacon) in the intervention study. The same syringol sulfates were also positively associated with recent or habitual consumption of smoked meat products in urine samples from participants of the EPIC cross-sectional study. These compounds showed good discriminative ability for smoked meat intake with receiver operator characteristic areas under the curve ranging from 0.78 to 0.86 and 0.74 to 0.79 for short-term and habitual intake, respectively. Conclusions Four novel syringol sulfates were identified as potential biomarkers of smoked meat intake and may be used to improve assessment of smoked meat intake in epidemiological studies. This trial was registered at clinicaltrials.gov as NCT03354130.

International audience; Cell fate maintenance is an integral part of plant cell differentiation and the production of functional cells, tissues, and organs. Fleshy fruit development is characterized by the accumulation of water and solutes in the enlarging cells of parenchymatous tissues. In tomato (Solanum lycopersicum), this process is associated with endoreduplication in mesocarp cells. The mechanisms that preserve this developmental program, once initiated, remain unknown. We show here that analysis of a previously identified tomato ethyl methanesulfonate-induced mutant that exhibits abnormal mesocarp cell differentiation could help elucidate determinants of fruit cell fate maintenance. We identified and validated the causal locus through mapping-by-sequencing and gene editing, respectively, and performed metabolic, cellular, and transcriptomic analyses of the mutant phenotype. The data indicate that disruption of the SlGBP1 gene, encoding GUANYLATE BINDING PROTEIN1, induces early termination of endoreduplication followed by late divisions of polyploid mesocarp cells, which consequently acquire the characteristics of young proliferative cells. This study reveals a crucial role of plant GBPs in the control of cell cycle genes, and thus, in cell fate maintenance. We propose that SlGBP1 acts as an inhibitor of cell division, a function conserved with the human hGBP-1 protein.

International audience

UMR 1332 - Equipe GFDF/OrFE/Meta; Key mechanisms controlling fruit weight and shape at the levels of meristem, ovary or very young fruit have already been identified using natural tomato diversity. We reasoned that new developmental modules prominent at later stages of fruit growth could be discovered by using new genetic and phenotypic diversity generated by saturated mutagenesis. Twelve fruit weight and tissue morphology mutants likely affected in late fruit growth were selected among thousands of fruit size and shape EMS mutants available in our tomato EMS mutant collection. Their thorough characterization at organ, tissue and cellular levels revealed two major clusters controlling fruit growth and tissue morphogenesis either through (i) the growth of all fruit tissues through isotropic cell expansion or (ii) only the growth of the pericarp through anisotropic cell expansion. These likely correspond to new cell expansion modules controlling fruit growth and tissue morphogenesis in tomato. Our study therefore opens the way for the identification of new gene regulatory networks controlling tomato fruit growth and morphology.

International audience; Micro-Tom tomato cultivar is particularly adapted to the development of genomic approaches in tomato. Here, we describe the culture of this plant in greenhouse, including climate regulation, seed sowing and watering, vegetative development, plant maintenance, including treatment of phytosanitary problems, and reproductive development.

Highlight The two tomato GDP-D-mannose epimerase isoforms play specific roles in cell wall biosynthesis and plant development but participate similarly in ascorbate biosynthesis., GDP-D-mannose epimerase (GME, EC 5.1.3.18) converts GDP-D-mannose to GDP-L-galactose, and is considered to be a central enzyme connecting the major ascorbate biosynthesis pathway to primary cell wall metabolism in higher plants. Our previous work demonstrated that GME is crucial for both ascorbate and cell wall biosynthesis in tomato. The aim of the present study was to investigate the respective role in ascorbate and cell wall biosynthesis of the two SlGME genes present in tomato by targeting each of them through an RNAi-silencing approach. Taken individually SlGME1 and SlGME2 allowed normal ascorbate accumulation in the leaf and fruits, thus suggesting the same function regarding ascorbate. However, SlGME1 and SlGME2 were shown to play distinct roles in cell wall biosynthesis, depending on the tissue considered. The RNAi-SlGME1 plants harbored small and poorly seeded fruits resulting from alterations of pollen development and of pollination process. In contrast, the RNAi-SlGME2 plants exhibited vegetative growth delay while fruits remained unaffected. Analysis of SlGME1- and SlGME2-silenced seeds and seedlings further showed that the dimerization state of pectin rhamnogalacturonan-II (RG-II) was altered only in the RNAi-SlGME2 lines. Taken together with the preferential expression of each SlGME gene in different tomato tissues, these results suggest sub-functionalization of SlGME1 and SlGME2 and their specialization for cell wall biosynthesis in specific tomato tissues.

National audience

Micro-Tom tomato cultivar is particularly adapted to the development of genomic approaches in tomato. Here, we describe the culture of this plant in greenhouse, including climate regulation, seed sowing and watering, vegetative development, plant maintenance, including treatment of phytosanitary problems, and reproductive development.

The interest of the tomato (Solanum lycopersicum) fruit has spread in plant science where it is used as the model for fleshy fruit. The valuable advantages of the tomato fruit are numerous: an ease of culture, a short generation time, a high knowledge with important resources, a sequenced genome, an ease for transforming…. The development of tomato fruit is a complex regulated process, divided in four main steps: cell division, cell expansion, turning and ripening. Each step is characterized by a phenotype resulting from changes at different cellular levels. Thus, gene expression, protein abundance, enzyme activities, metabolic fluxes and metabolite concentrations show significant changes during these steps. Thanks to recent technologies advances and in particular the development of ‘omics techniques’, such as genomic, transcriptomic, proteomic, metabolomic, the main cell components can now be analysed by high-throughput. In this context, the objective of my PhD was to perform a quantitative proteomic analysis of the tomato fruit development and then integrate omics data both by statistical analyses and by mathematical modelling. The first chapter focused on results obtained for the quantitative proteomic developed in collaboration with the PAPPSO platform (INRA, Gif-sur-Yvette). Samples were harvested at nine stages of tomato fruit development, total proteome was extracted and quantified by label-free LC-MS/MS. Then I searched for the most appropriate method, testing a set of filters on the data, to obtain an absolute label-free protein quantification from ion intensities (XIC). Finally, I obtained the absolute quantification of 2494 proteins using a method based on peptides intensity modelling. The quantification of proteins by LC-MS/MS was then validated by comparison with 32 enzymatic capacities used as proxy for protein abundance. The second chapter was dedicated to the results of integrative omics analyses throughout tomato fruit development. First, transcriptomic has been performed in collaboration with Genotoul GeT (Toulouse) and Usadel‘lab (RWTH Aachen University, Germany). Using spikes in the experimental design, more than 20000 transcripts have been quantitatively determined at the nine stages of development. Then, this absolute quantification of the tomato transcriptome has been cross-validated with 71 transcripts previously measured by qRT-PCR. Finally, we integrated the four omics datasets- transcriptome, proteome, metabolome and activome – in order to identify key variables of the tomato fruit development. For the four levels, analyses confirmed that the entrance in maturation phase was accompanied by major changes, and revealed a great similarity between the end and the beginning of development, especially in the energy metabolism. The third chapter focuses on modelling results of the protein translation based on the absolute quantification of transcriptomic and proteomic. To explain the decreasing correlation observed between proteins and transcripts concentration throughout development, we proposed a mathematical model of protein translation based on an ordinary differential equation and involving two rate constants (for synthesis and degradation of the protein). The resolution of this equation, validated by a quality criteria based on a closed confidence interval, led to the estimation of the rate constants for more than 1000 proteins. These results were then compared with previous published data reported for plants and more widely in eukaryotic cells. Finally, the last chapter describes all the materials and methods used to obtain the results presented in the manuscript.In the systems biology context, this work illustrates how integration of multiple omics datasets and mechanistic modelling based on absolute omics quantification can reveal new properties of cellular component., La tomate (Solanum lycopersicum) [...] présente de nombreux avantages : facilité de culture, temps de génération court, connaissances et ressources importantes, génome séquencé, facilité de transformation... Le développement du fruit est un procédé complexe hautement régulé et divisible en quatre étapes principales : la division cellulaire, l'expansion cellulaire, l’étape appelé « turning » et la maturation. Chaque étape est associée à un phénotype, qui lui-même découle de changements à différents niveaux cellulaires. [...]. Grâce aux récents progrès technologiques et en particulier au développement des «techniques omiques», comme la génomique, la transcriptomique, la protéomique, la métabolomique, les principaux composants cellulaires peuvent désormais être étudiés à haut densité. Dans ce contexte, l'objectif de mon doctorat était d'effectuer une analyse protéomique quantitative du développement du fruit de tomate puis d’intégrer les données «omiques» à la fois par des analyses statistiques et par la modélisation mathématique. Le premier chapitre rapporte les résultats de quantification du protéome de fruit de tomate réalisé en collaboration avec la plateforme PAPPSO (INRA, Gif-sur-Yvette). Des échantillons collectés à neuf stades de développement du fruit de tomate ont été extraits et le protéome quantifié, en absence de marquage, par chromatographie liquide couplée à la spectrométrie de masse (LC-MS/MS). Ensuite, j'ai cherché la méthode la plus adaptée, testant un ensemble de filtres sur les données, pour obtenir une quantification précise des protéines à partir des intensités ioniques (XIC). Au total, j’ai pu obtenir la quantification absolue de 2494 protéines en utilisant une méthode basée sur la modélisation de l'intensité des peptides. [...] Le deuxième chapitre est consacré aux résultats obtenus par analyses combinées d’«omiques» au cours du développement du fruit de tomate. La transcriptomique a été réalisée en collaboration avec Genotoul GeT (Toulouse) et le groupe Usadel (RWTH Aachen University, Allemagne). Grâce à l’ajout d’étalons internes, plus de 20000 transcrits ont été quantifiés de manière absolue à chacune des neuf étapes de développement. Cette quantification a ensuite été validée par comparaison avec des données de concentration de 71 transcrits précédemment obtenues par PCR quantitative. Enfin, nous avons cherché à intégrer les quatre niveaux de données - transcriptome, protéome, métabolome et activome- afin d‘identifier les principales variables associées au développement. Pour ces quatre niveaux, les analyses ont confirmé que l’entrée en maturation s’accompagne de changements majeurs et révélé une grande similarité entre la fin et le début du développement, notamment au niveau du métabolisme énergétique. Le troisième chapitre porte sur les résultats de modélisation de la traduction protéique obtenus grâce à la quantification absolue du transcriptome et du protéome. Afin d’expliquer la corrélation décroissante observée au cours du développement entre les concentrations en protéines et celles des transcrits correspondants, nous avons résolu un modèle mathématique de la traduction protéique basé sur une équation différentielle ordinaire et impliquant deux constantes de vitesse: pour la synthèse et la dégradation de la protéine. La résolution de cette équation, validée par un critère de qualité basé un intervalle de confiance fermé, a conduit à l'estimation de ces constantes pour plus de 1000 protéines. [...] Enfin le dernier chapitre décrit l’ensemble du matériel et des méthodes utilisées pour obtenir les différents résultats présentés dans le manuscrit. Dans le domaine de la biologie des systèmes, ce travail illustre comment l'intégration de multiples données «omiques» et la modélisation mécanistique basée sur la quantification absolue des «omiques» peut révéler de nouvelles propriétés des composants cellulaires.