Ecological and metabolic implications of the nurse effect of Maihueniopsis camachoi in the Atacama Desert.

Plant-plant positive interactions are key drivers of community structure. Yet, the underlying molecular mechanisms of facilitation processes remain unexplored. We investigated the 'nursing' effect of Maihueniopsis camachoi, a cactus that thrives in the Atacama Desert between c. 2800 and 3800 m above sea level. We hypothesised that an important protective factor is thermal amelioration of less cold-tolerant species with a corresponding impact on molecular phenotypes. To test this hypothesis, we compared plant cover and temperatures within the cactus foliage with open areas and modelled the effect of temperatures on plant distribution. We combined eco-metabolomics and machine learning to test the molecular consequences of this association. Multiple species benefited from the interaction with M. camachoi. A conspicuous example was the extended distribution of Atriplex imbricata to colder elevations in association with M. camachoi (400 m higher as compared to plants in open areas). Metabolomics identified 93 biochemical markers predicting the interaction status of A. imbricata with 79% accuracy, independently of year. These findings place M. camachoi as a key species in Atacama plant communities, driving local biodiversity with an impact on molecular phenotypes of nursed species. Our results support the stress-gradient hypothesis and provide pioneer insights into the metabolic consequences of facilitation.

Enzyme-based kinetic modelling of ASC-GSH cycle during tomato fruit development reveals the importance of reducing power and ROS availability.

The ascorbate-glutathione (ASC-GSH) cycle is at the heart of redox metabolism, linking the major redox buffers with central metabolism through the processing of reactive oxygen species (ROS) and pyridine nucleotide metabolism. Tomato fruit development is underpinned by changes in redox buffer contents and their associated enzyme capacities, but interactions between them remain unclear. Based on quantitative data obtained for the core redox metabolism, we built an enzyme-based kinetic model to calculate redox metabolite concentrations with their corresponding fluxes and control coefficients. Dynamic and associated regulations of the ASC-GSH cycle throughout the whole fruit development were analysed and pointed to a sequential metabolic control of redox fluxes by ASC synthesis, NAD(P)H and ROS availability depending on the developmental phase. Furthermore, we highlighted that monodehydroascorbate reductase and the availability of reducing power were found to be the main regulators of the redox state of ASC and GSH during fruit growth under optimal conditions. Our kinetic modelling approach indicated that tomato fruit development displayed growth phase-dependent redox metabolism linked with central metabolism via pyridine nucleotides and H2 O2 availability, while providing a new tool to the scientific community to investigate redox metabolism in fruits.

Soil metabolomics: A powerful tool for predicting and specifying pesticide sorption.

Sorption regulates the dispersion of pesticides from cropped areas to surrounding water bodies as well as their persistence. Assessing the risk of water contamination and evaluating the efficiency of mitigation measures, requires fine-resolution sorption data and a good knowledge of its drivers. This study aimed to assess the potential of a new approach combining chemometric and soil metabolomics to estimate the adsorption and desorption coefficients of a range of pesticides. It also aims to identify and characterise key components of soil organic matter (SOM) driving the sorption of these pesticides. We constituted a dataset of 43 soils from Tunisia, France and Guadeloupe (West Indies), covering extensive ranges of texture, organic carbon and pH. We performed untargeted soil metabolomics by liquid chromatography coupled with high-resolution mass spectrometry (UPLC-HRMS). We measured the adsorption and desorption coefficients of three pesticides namely glyphosate, 2,4-D and difenoconazole for these soils. We developed Partial Least Square Regression (PLSR) models for the prediction of the sorption coefficients from the RT-m/z matrix and conducted further ANOVA analyses to identify, annotate and characterise the most significant constituents of SOM in the PLSR models. The curated metabolomics matrix yielded 1213 metabolic markers. The prediction performance of the PLSR models was generally high for the adsorption coefficients Kdads (0.3 < R2 < 0.8) and for the desorption coefficients Kfdes (0.6 < R2 < 0.8) but low for ndes (0.03 < R2 < 0.3). The most significant features in the predictive models were annotated with a confidence level of 2 or 3. The molecular descriptors of these putative compounds suggest that the pool of SOM compounds driving glyphosate sorption is reduced compared to 2,4-D and difenoconazole, and these compounds are generally more polar. This approach can provide estimates of the adsorption and desorption coefficients of pesticides, including polar pesticide, for contrasted pedoclimates.

Genotype determines Arbutus unedo L. physiological and metabolomic responses to drought and recovery.

Strawberry tree (Arbutus unedo) is a small resilient species with a circum-Mediterranean distribution, high ecological relevance in southern European forests and with several economical applications. As most orchards are usually installed on marginal lands where plants usually face severe drought, selecting plants that can better cope with water restriction is critical, and a better understanding of the tolerance mechanisms is required. Strawberry tree plants under drought follow a typical isohydric strategy, by limiting transpiration through stomata closure. However, the contribution of genotype and its bio-geographic origin on plant performance needs clarification, as well as the involvement of a specific metabolic reactions associated with the mechanical response. To test this hypothesis, several eco-physiological and biochemical parameters were assessed on different genotypes, and the metabolic profiles studied, including important stress-related phytohormones, on plants under different water regimes (plants watered to 70% and 18% field capacity) and a recovery assay. A contrasting drought tolerance was found in plants from different genotypes, associated with physiological and metabolic responses. Metabolomics revealed more than 500 metabolic features were differentially accumulated, including abscisic and salicylic acids, for the genotype with better performance under drought (A4). This genotype also recovered faster when the imposed stress was interrupted, thus indicating the relevance of metabolic adaptation under water deficit conditions. By correlating carbon assimilation with identified metabolites, some proved to be satisfactory predictors of plant performance under drought and might be used for marker assisted breeding. Therefore, our study proves the importance of genotype as a major selection criterion of resistant plants to drought and provides empirical knowledge of the metabolic response involved. We also hypothesized the involvement of phenolics on response mechanisms under drought, which is worth to be explored to shed light on the metabolic pathways involved in plant response to water stress.

Impaired cell growth under ammonium stress explained by modeling the energy cost of vacuole expansion in tomato leaves.

Ammonium (NH4 + )-based fertilization efficiently mitigates the adverse effects of nitrogen fertilization on the environment. However, high concentrations of soil NH4 + provoke growth inhibition, partly caused by the reduction of cell enlargement and associated with modifications of cell composition, such as an increase of sugars and a decrease in organic acids. Cell expansion depends largely on the osmotic-driven enlargement of the vacuole. However, the involvement of subcellular compartmentation in the adaptation of plants to ammonium nutrition has received little attention, until now. To investigate this, tomato (Solanum lycopersicum) plants were cultivated under nitrate and ammonium nutrition and the fourth leaf was harvested at seven developmental stages. The vacuolar expansion was monitored and metabolites and inorganic ion contents, together with intracellular pH, were determined. A data-constrained model was constructed to estimate subcellular concentrations of major metabolites and ions. It was first validated at the three latter developmental stages by comparison with subcellular concentrations obtained experimentally using non-aqueous fractionation. Then, the model was used to estimate the subcellular concentrations at the seven developmental stages and the net vacuolar uptake of solutes along the developmental series. Our results showed ammonium nutrition provokes an acidification of the vacuole and a reduction in the flux of solutes into the vacuoles. Overall, analysis of the subcellular compartmentation reveals a mechanism behind leaf growth inhibition under ammonium stress linked to the higher energy cost of vacuole expansion, as a result of alterations in pH, the inhibition of glycolysis routes and the depletion of organic acids.

PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management.

INTRODUCTION: Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories. OBJECTIVES: To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management. METHODS: We developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles. RESULTS: PeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases. CONCLUSION: PeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest .

Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience.

Current crop yield of the best ideotypes is stagnating and threatened by climate change. In this scenario, understanding wild plant adaptations in extreme ecosystems offers an opportunity to learn about new mechanisms for resilience. Previous studies have shown species specificity for metabolites involved in plant adaptation to harsh environments. Here, we combined multispecies ecological metabolomics and machine learning-based generalized linear model predictions to link the metabolome to the plant environment in a set of 24 species belonging to 14 families growing along an altitudinal gradient in the Atacama Desert. Thirty-nine common compounds predicted the plant environment with 79% accuracy, thus establishing the plant metabolome as an excellent integrative predictor of environmental fluctuations. These metabolites were independent of the species and validated both statistically and biologically using an independent dataset from a different sampling year. Thereafter, using multiblock predictive regressions, metabolites were linked to climatic and edaphic stressors such as freezing temperature, water deficit and high solar irradiance. These findings indicate that plants from different evolutionary trajectories use a generic metabolic toolkit to face extreme environments. These core metabolites, also present in agronomic species, provide a unique metabolic goldmine for improving crop performances under abiotic pressure.

Metabolomics to Exploit the Primed Immune System of Tomato Fruit.

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.

Get the Balance Right: ROS Homeostasis and Redox Signalling in Fruit.

Plant central metabolism generates reactive oxygen species (ROS), which are key regulators that mediate signalling pathways involved in developmental processes and plant responses to environmental fluctuations. These highly reactive metabolites can lead to cellular damage when the reduction-oxidation (redox) homeostasis becomes unbalanced. Whilst decades of research have studied redox homeostasis in leaves, fundamental knowledge in fruit biology is still fragmentary. This is even more surprising when considering the natural profusion of fruit antioxidants that can process ROS and benefit human health. In this review, we explore redox biology in fruit and provide an overview of fruit antioxidants with recent examples. We further examine the central role of the redox hub in signalling during development and stress, with particular emphasis on ascorbate, also referred to as vitamin C. Progress in understanding the molecular mechanisms involved in the redox regulations that are linked to central metabolism and stress pathways will help to define novel strategies for optimising fruit nutritional quality, fruit production and storage.