Modeling Protein Destiny in Developing Fruit

Belouah, Isma; Nazaret, Christine; Pétriacq, Pierre; Prigent, Sylvain; Bénard, Camille; Mengin, Virginie; Blein-Nicolas, Mélisande; Denton, Alisandra K.; Augé, Ségolène; Bouchez, Olivier; Mazat, Jean‐Pierre; Stitt, Mark; Usadel, Björn; Zivy, Michel; Beauvoit, Bertrand; Gibon, Yves; Colombié, Sophie

doi:10.1104/pp.19.00086

Cited by 25 publications

(26 citation statements)

References 70 publications

(85 reference statements)

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“…This agrees with previous phenotyping and modelling studies on tomato that demonstrate metabolic shifts in carbon metabolism in the growing fruit [25,28,29,31]. Furthermore, it has been recently confirmed through transcriptomics and proteomics that the developing fruit not only undergoes metabolic shifts in central pathways, but also redox metabolism, such as for pyridine nucleotides that are detrimental to energy homeostasis [27,32,33]. However, major questions remain regarding the nature and dynamics of shifts in central metabolism upon pathogen inoculation.…”

Section: Discussionsupporting

confidence: 89%

“…PCA explained 83% of the maximal variance in the dataset and resulted in a separation of fruit by developmental characteristics (i.e., the first and second fruit versus the third fruit) rather than by pathosystems ( Figure 3B). Hence, this multivariate differentiation indicates that the profiles of primary metabolites mostly respond to the developmental stage of the fruit, which supports the idea that central metabolism is tuned to fruit growth [27][28][29]. Complementarily, two-factor ANOVA (P < 0.05) only generated significant markers for the inoculation factor (4; 36%), including sucrose, fructose, glutamate and fumarate (Table 1 and Figure S1).…”

Section: Global Metabolomics After Baba Treatment and After Inoculationsupporting

confidence: 75%

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Metabolomics to Exploit the Primed Immune System of Tomato Fruit

et al. 2020

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Tomato is a major crop suffering substantial yield losses from diseases, as fruit decay at a postharvest level can claim up to 50% of the total production worldwide. Due to the environmental risks of fungicides, there is an increasing interest in exploiting plant immunity through priming, which is an adaptive strategy that improves plant defensive capacity by stimulating induced mechanisms. Broad-spectrum defence priming can be triggered by the compound ß-aminobutyric acid (BABA). In tomato plants, BABA induces resistance against various fungal and bacterial pathogens and different methods of application result in durable protection. Here, we demonstrate that the treatment of tomato plants with BABA resulted in a durable induced resistance in tomato fruit against Botrytis cinerea, Phytophthora infestans and Pseudomonas syringae. Targeted and untargeted metabolomics were used to investigate the metabolic regulations that underpin the priming of tomato fruit against pathogenic microbes that present different infection strategies. Metabolomic analyses revealed major changes after BABA treatment and after inoculation. Remarkably, primed responses seemed specific to the type of infection, rather than showing a common fingerprint of BABA-induced priming. Furthermore, top-down modelling from the detected metabolic markers allowed for the accurate prediction of the measured resistance to fruit pathogens and demonstrated that soluble sugars are essential to predict resistance to fruit pathogens. Altogether, our results demonstrate that metabolomics is particularly insightful for a better understanding of defence priming in fruit. Further experiments are underway in order to identify key metabolites that mediate broad-spectrum BABA-induced priming in tomato fruit.

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Section: Discussionsupporting

confidence: 89%

Section: Global Metabolomics After Baba Treatment and After Inoculationsupporting

confidence: 75%

Metabolomics to Exploit the Primed Immune System of Tomato Fruit

et al. 2020

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“…These observations can be caused by paralog exchanges or by PTMs. Paralog exchanges are likely considering independent reports showing that paired transcript translation and protein degradation rates of cytosolic-RPs from tomato Solanum lycopersicum are high ( Belouah et al., 2019 ) and cytosolic RPs of Arabidopsis have a high standard deviation of the protein degradation rates ( Li et al., 2017a ). These studies suggest that a potential mechanism of ribosome remodeling exists even though RPs are in general stable and long-lived ( Li et al., 2017a ).…”

Section: Protein Composition Of the Cytosolic Ribosomementioning

confidence: 99%

Systematic Review of Plant Ribosome Heterogeneity and Specialization

et al. 2020

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Plants dedicate a high amount of energy and resources to the production of ribosomes. Historically, these multi-protein ribosome complexes have been considered static protein synthesis machines that are not subject to extensive regulation but only read mRNA and produce polypeptides accordingly. New and increasing evidence across various model organisms demonstrated the heterogeneous nature of ribosomes. This heterogeneity can constitute specialized ribosomes that regulate mRNA translation and control protein synthesis. A prominent example of ribosome heterogeneity is seen in the model plant, Arabidopsis thaliana , which, due to genome duplications, has multiple paralogs of each ribosomal protein (RP) gene. We support the notion of plant evolution directing high RP paralog divergence toward functional heterogeneity, underpinned in part by a vast resource of ribosome mutants that suggest specialization extends beyond the pleiotropic effects of single structural RPs or RP paralogs. Thus, Arabidopsis is a highly suitable model to study this phenomenon. Arabidopsis enables reverse genetics approaches that could provide evidence of ribosome specialization. In this review, we critically assess evidence of plant ribosome specialization and highlight steps along ribosome biogenesis in which heterogeneity may arise, filling the knowledge gaps in plant science by providing advanced insights from the human or yeast fields. We propose a data analysis pipeline that infers the heterogeneity of ribosome complexes and deviations from canonical structural compositions linked to stress events. This analysis pipeline can be extrapolated and enhanced by combination with other high-throughput methodologies, such as proteomics. Technologies, such as kinetic mass spectrometry and ribosome profiling, will be necessary to resolve the temporal and spatial aspects of translational regulation while the functional features of ribosomal subpopulations will become clear with the combination of reverse genetics and systems biology approaches.

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“…This is performed by integrating transcriptomics and proteomics data sets of nine tomato developmental stages using ordinary differential equations (ODE) to obtain rate constants for translation (k t ) and degradation (k d ). The result suggests that the equation reliably predicts the expression of nearly 50% of 2,400 transcript-protein pairs from the study and that the protein level was regulated strongly by the translation rate rather than degradation (Belouah et al, 2019).…”

Section: Differential Analysismentioning

confidence: 80%

“…Differential analysis has been applied to various plant and fruit studies ( Koç et al., 2018 ; Wang et al., 2018 ; Belouah et al., 2019 ) and can be divided into either non-targeted or targeted pathway studies. One recent example of the former (non-targeted pathway) approach is the development of differential equation for protein density during tomato ripening ( Belouah et al., 2019 ). This is performed by integrating transcriptomics and proteomics data sets of nine tomato developmental stages using ordinary differential equations (ODE) to obtain rate constants for translation ( k t ) and degradation ( k d ).…”

Section: Level 3 Moi: Mathematical-based Approachmentioning

confidence: 99%

Systematic Multi-Omics Integration (MOI) Approach in Plant Systems Biology

et al. 2020

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Across all facets of biology, the rapid progress in high-throughput data generation has enabled us to perform multi-omics systems biology research. Transcriptomics, proteomics, and metabolomics data can answer targeted biological questions regarding the expression of transcripts, proteins, and metabolites, independently, but a systematic multi-omics integration (MOI) can comprehensively assimilate, annotate, and model these large data sets. Previous MOI studies and reviews have detailed its usage and practicality on various organisms including human, animals, microbes, and plants. Plants are especially challenging due to large poorly annotated genomes, multi-organelles, and diverse secondary metabolites. Hence, constructive and methodological guidelines on how to perform MOI for plants are needed, particularly for researchers newly embarking on this topic. In this review, we thoroughly classify multi-omics studies on plants and verify workflows to ensure successful omics integration with accurate data representation. We also propose three levels of MOI, namely element-based (level 1), pathway-based (level 2), and mathematical-based integration (level 3). These MOI levels are described in relation to recent publications and tools, to highlight their practicality and function. The drawbacks and limitations of these MOI are also discussed for future improvement toward more amenable strategies in plant systems biology.

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Modeling Protein Destiny in Developing Fruit

Cited by 25 publications

References 70 publications

Metabolomics to Exploit the Primed Immune System of Tomato Fruit

Metabolomics to Exploit the Primed Immune System of Tomato Fruit

Systematic Review of Plant Ribosome Heterogeneity and Specialization

Systematic Multi-Omics Integration (MOI) Approach in Plant Systems Biology

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