Multi-omics quantitative data of tomato fruit unveils regulation modes of least variable metabolites.

BACKGROUND: The composition of ripe fruits depends on various metabolites which content evolves greatly throughout fruit development and may be influenced by the environment. The corresponding metabolism regulations have been widely described in tomato during fruit growth and ripening. However, the regulation of other metabolites that do not show large changes in content have scarcely been studied. RESULTS: We analysed the metabolites of tomato fruits collected on different trusses during fruit development, using complementary analytical strategies. We identified the 22 least variable metabolites, based on their coefficients of variation. We first verified that they had a limited functional link with the least variable proteins and transcripts. We then posited that metabolite contents could be stabilized through complex regulations and combined their data with the quantitative proteome or transcriptome data, using sparse partial-least-square analyses. This showed shared regulations between several metabolites, which interestingly remained linked to early fruit development. We also examined regulations in specific metabolites using correlations with individual proteins and transcripts, which revealed that a stable metabolite does not always correlate with proteins and transcripts of its known related pathways. CONCLUSIONS: The regulation of the least variable metabolites was then interpreted regarding their roles as hubs in metabolic pathways or as signalling molecules.

NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows.

INTRODUCTION: Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling. OBJECTIVES: An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) and operator on quantification trueness and precision. METHODS: A synthetic urine containing 32 compounds was prepared. One site prepared the urine and calibration samples, and performed NMR acquisition. NMR spectra were acquired with two pulse sequences including water suppression used in routine analyses. The pre-processed spectra were sent to the other sites where each operator quantified the metabolites using internal referencing or external calibration, and his/her favourite in-house, open-access or commercial NMR tool. RESULTS: For 1D NMR measurements with solvent presaturation during the recovery delay (zgpr), 20 metabolites were successfully quantified by all processing strategies. Some metabolites could not be quantified by some methods. For internal referencing with TSP, only one half of the metabolites were quantified with a trueness below 5%. With peak integration and external calibration, about 90% of the metabolites were quantified with a trueness below 5%. The NMRProcFlow integration module allowed the quantification of several additional metabolites. The number of quantified metabolites and quantification trueness improved for some metabolites with deconvolution tools. Trueness and precision were not significantly different between zgpr- and NOESYpr-based spectra for about 70% of the variables. CONCLUSION: External calibration performed better than TSP internal referencing. Inter-laboratory tests are useful when choosing to better rationalize the choice of quantification tools for NMR-based metabolomic profiling and confirm the value of spectra deconvolution tools.

The Tomato Guanylate-Binding Protein SlGBP1 Enables Fruit Tissue Differentiation by Maintaining Endopolyploid Cells in a Non-Proliferative State.

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.

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 .

Development, Validation, and Use of 1H-NMR Spectroscopy for Evaluating the Quality of Acerola-Based Food Supplements and Quantifying Ascorbic Acid.

Acerola (Malpighia emarginata D.C.) is an exotic fruit with high agro-industrial potential due to its high content of ascorbic acid (AA), phenolic compounds, and carotenoid pigments. Acerola fruit is processed into concentrated juice or powder to be incorporated into food supplements. The ascorbic acid content of concentrated juice or powders must be controlled and well assessed. Therefore, the development of optimal methods and procedures for the rapid and accurate determination of the ascorbic acid content in juice concentrate and juice powder remains of considerable commercial interest. NMR spectroscopy is currently a powerful spectroscopic tool for the qualitative and quantitative analysis of molecules of all types and sizes. Firstly, this article presents the NMR-based metabolomic profiling of acerola juice and concentrate powder to describe and compare their composition. Thirty-six metabolites were identified. The AA over choline ratio and the NMR metabolomic profiles could be used for authentication in the future. Secondly, a rapid (8 min), reliable, and non-destructive method for the quantification of ascorbic acid by 1D 1H-NMR spectroscopy was developed and validated. The LOD and LOQ were 0.05 and 0.15 mg/mL, respectively. These two approaches could be combined to better characterize ingredients derived from acerola and incorporated into food supplements.

Omics Data Reveal Putative Regulators of Einkorn Grain Protein Composition under Sulfur Deficiency.

Understanding the molecular mechanisms controlling the accumulation of grain storage proteins in response to nitrogen (N) and sulfur (S) nutrition is essential to improve cereal grain nutritional and functional properties. Here, we studied the grain transcriptome and metabolome responses to postanthesis N and S supply for the diploid wheat einkorn (Triticum monococcum). During grain filling, 848 transcripts and 24 metabolites were differentially accumulated in response to N and S availability. The accumulation of total free amino acids per grain and the expression levels of 241 genes showed significant modifications during most of the grain filling period and were upregulated in response to S deficiency. Among them, 24 transcripts strongly responded to S deficiency and were identified in coexpression network analyses as potential coordinators of the grain response to N and S supply. Sulfate transporters and genes involved in sulfate and Met metabolism were upregulated, suggesting regulation of the pool of free amino acids and of the grain N-to-S ratio. Several genes highlighted in this study might limit the impact of S deficiency on the accumulation of grain storage proteins.

Maize metabolome and proteome responses to controlled cold stress partly mimic early-sowing effects in the field and differ from those of Arabidopsis.

In Northern Europe, sowing maize one-month earlier than current agricultural practices may lead to moderate chilling damage. However, studies of the metabolic responses to low, non-freezing, temperatures remain scarce. Here, genetically-diverse maize hybrids (Zea mays, dent inbred lines crossed with a flint inbred line) were cultivated in a growth chamber at optimal temperature and then three decreasing temperatures for 2 days each, as well as in the field. Leaf metabolomic and proteomic profiles were determined. In the growth chamber, 50% of metabolites and 18% of proteins changed between 20 and 16°C. These maize responses, partly differing from those of Arabidopsis to short-term chilling, were mapped on genome-wide metabolic maps. Several metabolites and proteins showed similar variation for all temperature decreases: seven MS-based metabolite signatures and two proteins involved in photosynthesis decreased continuously. Several increasing metabolites or proteins in the growth-chamber chilling conditions showed similar trends in the early-sowing field experiment, including trans-aconitate, three hydroxycinnamate derivatives, a benzoxazinoid, a sucrose synthase, lethal leaf-spot 1 protein, an allene oxide synthase, several glutathione transferases and peroxidases. Hybrid groups based on field biomass were used to search for the metabolite or protein responses differentiating them in growth-chamber conditions, which could be of interest for breeding.

MRSI vs CEST MRI to understand tomato metabolism in ripening fruit: is there a better contrast?

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.

Hyperpolarized NMR Metabolomics at Natural 13C Abundance.

Metabolomics plays a pivotal role in systems biology, and NMR is a central tool with high precision and exceptional resolution of chemical information. Most NMR metabolomic studies are based on 1H 1D spectroscopy, severely limited by peak overlap. 13C NMR benefits from a larger signal dispersion but is barely used in metabolomics due to ca. 6000-fold lower sensitivity. We introduce a new approach, based on hyperpolarized 13C NMR at natural abundance, that circumvents this limitation. A new untargeted NMR-based metabolomic workflow based on dissolution dynamic nuclear polarization (d-DNP) for the first time enabled hyperpolarized natural abundance 13C metabolomics. Statistical analysis of resulting hyperpolarized 13C data distinguishes two groups of plant (tomato) extracts and highlights biomarkers, in full agreement with previous results on the same biological model. We also optimize parameters of the semiautomated d-DNP system suitable for high-throughput studies.

Biomass composition explains fruit relative growth rate and discriminates climacteric from non-climacteric species.

Fleshy fruits are very varied, whether in terms of their composition, physiology, or rate and duration of growth. To understand the mechanisms that link metabolism to phenotypes, which would help the targeting of breeding strategies, we compared eight fleshy fruit species during development and ripening. Three herbaceous (eggplant, pepper, and cucumber), three tree (apple, peach, and clementine) and two vine (kiwifruit and grape) species were selected for their diversity. Fruit fresh weight and biomass composition, including the major soluble and insoluble components, were determined throughout fruit development and ripening. Best-fitting models of fruit weight were used to estimate relative growth rate (RGR), which was significantly correlated with several biomass components, especially protein content (R=84), stearate (R=0.72), palmitate (R=0.72), and lignocerate (R=0.68). The strong link between biomass composition and RGR was further evidenced by generalized linear models that predicted RGR with R-values exceeding 0.9. Comparison of the fruit also showed that climacteric fruit (apple, peach, kiwifruit) contained more non-cellulosic cell-wall glucose and fucose, and more starch, than non-climacteric fruit. The rate of starch net accumulation was also higher in climacteric fruit. These results suggest that the way biomass is constructed has a major influence on performance, especially growth rate.

Proton-NMR Metabolomics of Rainbow Trout Fed a Plant-Based Diet Supplemented with Graded Levels of a Protein-Rich Yeast Fraction Reveal Several Metabolic Processes Involved in Growth.

BACKGROUND: Plant raw materials are commonly used in aquafeeds, as marine resources are unsustainable. However, full plant-based diets lead to poorer fish growth performance. OBJECTIVE: We aimed to understand the metabolic effects of a yeast fraction as a protein supplement in a plant-based diet and to integrate such effects with phenotypic traits as a new approach to assess the interest of this raw material. METHODS: Juvenile (49 g) rainbow trout (Oncorhynchus mykiss) were fed graded levels of a yeast protein-rich fraction (5% YST05, 10% YST10, 15% YST15) in a plant-based diet (PB) for 84 d. Final body weight, feed conversion ratio, and hepatosomatic and viscerosomatic indexes were measured. Plasma, liver, and muscle 1H-NMR fingerprints were analyzed with principal component analyses, and their metabolite patterns were clustered according to the yeast level to identify concomitant metabolic effects. A regression modeling approach was used to predict tissue metabolite changes from plasma fingerprints. RESULTS: In tissues, the patterns of metabolite changes followed either linear trends with the gradual inclusion of a yeast fraction (2 patterns out of 6 in muscle, 1 in liver) or quadratic trends (4 patterns in muscle, 5 in liver). Muscle aspartate and glucose (395 and 138% maximum increase in relative content compared with PB, respectively) revealing modification in energy metabolism, as well as modification of liver betaine (163% maximum increase) and muscle histidine (57% maximum decrease) related functions, indicates that the yeast fraction could improve growth in several ways. The highest correlation between measured and predicted metabolite intensities in a tissue based on plasma fingerprints was observed for betaine in liver (r = 0.80). CONCLUSIONS: These findings herald a new approach to assess the plurality of metabolic effects induced by diets and establish the optimal level of raw materials. They open the way for using plasma as a noninvasive matrix in trout nutrition studies.

Metabolomic characterization of sunflower leaf allows discriminating genotype groups or stress levels with a minimal set of metabolic markers.

INTRODUCTION: Plant and crop metabolomic analyses may be used to study metabolism across genetic and environmental diversity. Complementary analytical strategies are useful for investigating metabolic changes and searching for biomarkers of response or performance. METHODS AND OBJECTIVES: The experimental material consisted in eight sunflower lines with two line status, four restorers (R, used as males) and four maintainers (B, corresponding to females) routinely used for sunflower hybrid varietal production, respectively to complement or maintain the cytoplasmic male sterility PET1. These lines were either irrigated at full soil capacity (WW) or submitted to drought stress (DS). Our aim was to combine targeted and non-targeted metabolomics to characterize sunflower leaf composition in order to investigate the effect of line status genotypes and environmental conditions and to find the best and smallest set of biomarkers for line status and stress response using a custom-made process of variables selection. RESULTS: Five hundred and eighty-eight metabolic variables were measured by using complementary analytical methods such as 1H-NMR, MS-based profiles and targeted analyses of major metabolites. Based on statistical analyses, a limited number of markers were able to separate WW and DS samples in a more discriminant manner than previously published physiological data. Another metabolic marker set was able to discriminate line status. CONCLUSION: This study underlines the potential of metabolic markers for discriminating genotype groups and environmental conditions. Their potential use for prediction is discussed.

Optimizing 1D 1H-NMR profiling of plant samples for high throughput analysis: extract preparation, standardization, automation and spectra processing.

INTRODUCTION: Proton nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomic profiling has a range of applications in plant sciences. OBJECTIVES: The aim of the present work is to provide advice for minimizing uncontrolled variability in plant sample preparation before and during NMR metabolomic profiling, taking into account sample composition, including its specificity in terms of pH and paramagnetic ion concentrations, and NMR spectrometer performances. METHODS: An automation of spectrometer preparation routine standardization before NMR acquisition campaign was implemented and tested on three plant sample sets (extracts of durum wheat spikelet, Arabidopsis leaf and root, and flax leaf, root and stem). We performed 1H-NMR spectroscopy in three different sites on the wheat sample set utilizing instruments from two manufacturers with different probes and magnetic field strengths. The three collections of spectra were processed separately with the NMRProcFlow web tool using intelligent bucketing, and the resulting buckets were subjected to multivariate analysis. RESULTS: Comparability of large- (Arabidopsis) and medium-size (flax) datasets measured at 600 MHz and from the wheat sample set recorded at the three sites (400, 500 and 600 MHz) was exceptionally good in terms of spectral quality. The coefficient of variation of the full width at half maximum (FWHM) and the signal-to-noise ratio (S/N) of two selected peaks was comprised between 5 and 10% depending on the size of sample set and the spectrometer field. EDTA addition improved citrate and malate resonance patterns for wheat sample sets. A collection of 22 samples of wheat spikelet extracts was used as a proof of concept and showed that the data collected at the three sites on instruments of different field strengths and manufacturers yielded the same discrimination pattern of the biological groups. CONCLUSION: Standardization or automation of several steps from extract preparation to data reduction improves data quality for small to large collections of plant samples of different origins.

nmrML: A Community Supported Open Data Standard for the Description, Storage, and Exchange of NMR Data.

NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.

Mycotoxin Biosynthesis and Central Metabolism Are Two Interlinked Pathways in Fusarium graminearum, as Demonstrated by the Extensive Metabolic Changes Induced by Caffeic Acid Exposure.

Fusarium graminearum is a major plant pathogen that causes devastating diseases of cereals and produces type B trichothecene (TCTB) mycotoxins in infected grains. A comprehensive understanding of the molecular and biochemical mechanisms underlying the regulation of TCTB biosynthesis is required for improving strategies to control the TCTB contamination of crops and ensuring that these strategies do not favor the production of other toxic metabolites by F. graminearum Elucidation of the association of TCTB biosynthesis with other central and specialized processes was the focus of this study. Combined 1H nuclear magnetic resonance (1H NMR) and liquid chromatography-quadrupole time of flight-mass spectrometry (LC-QTOF-MS) analyses were used to compare the exo- and endometabolomes of F. graminearum grown under toxin-inducing and -repressing caffeic acid conditions. Ninety-five metabolites were putatively or unambiguously identified, including 26 primary and 69 specialized metabolites. Our data demonstrated that the inhibition of TCTB production induced by caffeic acid exposure was associated with significant changes in the secondary and primary metabolism of F. graminearum, although the fungal growth was not affected. The main metabolic changes were an increase in the accumulation of several polyketides, including toxic ones, alterations in the tricarboxylic organic acid cycle, and modifications in the metabolism of several amino acids and sugars. While these findings provide insights into the mechanisms that govern the inhibition of TCTB production by caffeic acid, they also demonstrate the interdependence between the biosynthetic pathway of TCTB and several primary and specialized metabolic pathways. These results provide further evidence of the multifaceted role of TCTB in the life cycle of F. graminearumIMPORTANCEFusarium graminearum is a major plant pathogen that causes devastating diseases of cereal crops and produces type B trichothecene (TCTB) mycotoxins in infected grains. The best way to restrict consumer exposure to TCTB is to limit their production before harvest, which requires increasing the knowledge on the mechanisms that regulate their biosynthesis. Using a metabolomics approach, we investigated the interconnection between the TCTB production pathway and several fungal metabolic pathways. We demonstrated that alteration in the TCTB biosynthetic pathway can have a significant impact on other metabolic pathways, including the biosynthesis of toxic polyketides, and vice versa. These findings open new avenues for identifying fungal targets for the design of molecules with antimycotoxin properties and therefore improving sustainable strategies to fight against diseases caused by F. graminearum Our data further demonstrate that analyses should consider all fungal toxic metabolites rather than the targeted family of mycotoxins when assessing the efficacy of control strategies.

Characterizing alternative feeds for rainbow trout (O. mykiss) by 1H NMR metabolomics.

INTRODUCTION: Fish feed formulations are constantly evolving to improve the quality of diets for farmed fish and to ensure the sustainability of the aquaculture sector. Nowadays, insect, microalgae and yeast are feedstuff candidates for new feeds. However, the characterization of aquafeed is still based on proximate and targeted analyses which may not be sufficient to assess feed quality. OBJECTIVES: Our aim was to highlight the soluble compounds that specifically differ between selected plant-based feeds complemented with alternative feedstuffs and discuss their origin and potential for fish nutrition. METHODS: A growth trial was carried out to evaluate growth performances and feed conversion ratios of fish fed plant-based, commercial, insect, spirulina and yeast feeds. 1H NMR metabolomics profiling of each feed was performed using a CPMG sequence on polar extracts. Spectra were processed, and data were analyzed using multivariate and univariate analyses to compare alternative feeds to a plant-based feed. RESULTS: Fish fed insect or yeast feed showed the best growth performances associated with the lowest feed conversion ratios compared to plant-based feed. Soluble compound 1H NMR profiles of insect and spirulina alternative feeds differed significantly from the plant-based one that clustered with yeast feed. In insect and spirulina feeds, specific differences compared to plant-based feed concerned glycerol and 3-hydroxybutyrate, respectively. CONCLUSION: This strategy based on compositional differences between plant-based and alternative feeds can be useful for detecting compounds unsuspected until now that could impact fish metabolism.

Characterization of GMO or glyphosate effects on the composition of maize grain and maize-based diet for rat feeding.

INTRODUCTION: In addition to classical targeted biochemical analyses, metabolomic analyses seem pertinent to reveal expected as well as unexpected compositional differences between plant genetically modified organisms (GMO) and non-GMO samples. Data previously published in the existing literature led to divergent conclusions on the effect of maize transgenes on grain compositional changes and feeding effects. Therefore, a new study examining field-grown harvested products and feeds derived from them remains useful. OBJECTIVES: Our aim was to use a metabolomics approach to characterize grain and grain-based diet compositional changes for two GMO events, one involving Bacillus thuringiensis toxin to provide insect resistance and the other one conferring herbicide tolerance by detoxification of glyphosate. We also investigated the potential compositional modifications induced by the use of a glyphosate-based herbicide on the transgenic line conferring glyphosate tolerance. RESULTS: The majority of statistically significant differences in grain composition, evidenced by the use of 1H-NMR profiling of polar extracts and LC-ESI-QTOF-MS profiling of semi-polar extracts, could be attributed to the combined effect of genotype and environment. In comparison, transgene and glyphosate effects remained limited in grain for the compound families studied. Some but not all compositional changes observed in grain were also detected in grain-based diets formulated for rats. CONCLUSION: Only part of the data previously published in the existing literature on maize grains of plants with the same GMO events could be reproduced in our experiment. All spectra have been deposited in a repository freely accessible to the public. Our grain and diet characterization opened the way for an in depth study of the effects of these diets on rat health.

Metabotyping of 30 maize hybrids under early-sowing conditions reveals potential marker-metabolites for breeding.

INTRODUCTION: In Northern Europe, maize early-sowing used to maximize yield may lead to moderate damages of seedlings due to chilling without visual phenotypes. Genetic studies and breeding for chilling tolerance remain necessary, and metabolic markers would be particularly useful in this context. OBJECTIVES: Using an untargeted metabolomic approach on a collection of maize hybrids, our aim was to identify metabolite signatures and/or metabolites associated with chilling responses at the vegetative stage, to search for metabolites differentiating groups of hybrids based on silage-earliness, and to search for marker-metabolites correlated with aerial biomass. METHODS: Thirty genetically-diverse maize dent inbred-lines (Zea mays) crossed to a flint inbred-line were sown in a field to assess metabolite profiles upon cold treatment induced by a modification of sowing date, and characterized with climatic measurements and phenotyping. RESULTS: NMR- and LC-MS-based metabolomic profiling revealed the biological variation of primary and specialized metabolites in young leaves of plants before flowering-stage. The effect of early-sowing on leaf composition was larger than that of genotype, and several metabolites were associated to sowing response. The metabolic distances between genotypes based on leaf compositional data were not related to the genotype admixture groups, and their variability was lower under early-sowing than normal-sowing. Several metabolites or metabolite-features were related to silage-earliness groups in the normal-sowing condition, some of which were confirmed the following year. Correlation networks involving metabolites and aerial biomass suggested marker-metabolites for breeding for chilling tolerance. CONCLUSION: After validation in other experiments and larger genotype panels, these marker-metabolites can contribute to breeding.

The peach HECATE3-like gene FLESHY plays a double role during fruit development.

Tight control of cell/tissue identity is essential for a correct and functional organ patterning, an important component of overall fruit development and eventual maturation and ripening. Despite many investigations regarding the molecular determinants of cell identity in fruits of different species, a useful model able to depict the regulatory networks governing this relevant part of fruit development is still missing. Here we described the peach fruit as a system to link the phenotype of a slow ripening (SR) selection to an altered transcriptional regulation of genes involved in determination of mesocarp cell identity providing insight toward molecular regulation of fruit tissue formation. Morpho-anatomical observations and metabolomics analyses performed during fruit development on the reference cultivar Fantasia, compared to SR, revealed that the mesocarp of SR maintained typical immaturity traits (e.g. small cell size, high amino acid contents and reduced sucrose) throughout development, along with a strong alteration of phenylpropanoid contents, resulting in accumulation of phenylalanine and lignin. These findings suggest that the SR mesocarp is phenotypically similar to a lignifying endocarp. To test this hypothesis, the expression of genes putatively involved in determination of drupe tissues identity was assessed. Among these, the peach HEC3-like gene FLESHY showed a strongly altered expression profile consistent with pit hardening and fruit ripening, generated at a post-transcriptional level. A double function for FLESHY in channelling the phenylpropanoid pathway to either lignin or flavour/aroma is suggested, along with its possible role in triggering auxin-ethylene cross talk at the start of ripening.

Highly Repeatable Dissolution Dynamic Nuclear Polarization for Heteronuclear NMR Metabolomics.

At natural (13)C abundance, metabolomics based on heteronuclear NMR is limited by sensitivity. We have recently demonstrated how hyperpolarization by dissolution dynamic nuclear polarization (D-DNP) assisted by cross-polarization (CP) provides a reliable way of enhancing the sensitivity of heteronuclear NMR in dilute mixtures of metabolites. In this Technical Note, we evaluate the precision of this experimental approach, a critical point for applications to metabolomics. The higher the repeatability, the greater the likelihood that one can detect small biologically relevant differences between samples. The average repeatability of our state-of-the-art D-DNP NMR equipment for samples of metabolomic relevance (20 mg dry weight tomato extracts) is 3.6% for signals above the limit of quantification (LOQ) and 6.4% when all the signals above the limit of detection (LOD) are taken into account. This first report on the repeatability of D-DNP highlights the compatibility of the technique with the requirements of metabolomics and confirms its potential as an analytical tool for such applications.