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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., (© 2023. The Author(s).)

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 ., (© 2022. The Author(s).)

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 1 H 1D spectroscopy, severely limited by peak overlap. 13 C 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 13 C 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 13 C metabolomics. Statistical analysis of resulting hyperpolarized 13 C 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.

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., (Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.)

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. 1 H 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 1 H 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.

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.

Yield formation in regions with intermittent drought periods depends on the plant's ability to recover after cessation of the stress. The present work assessed differences in metabolic recovery of leaves and roots of drought-stressed sugar beets with high temporal resolution. Plants were subjected to drought for 13 days, and rewatered for 12 days. At one to two-day intervals, plant material was harvested for untargeted 1H-NMR metabolomic profiling, targeted analyses of hexose-phosphates, starch, amino acids, nitrate and proteins, and physiological measurements including relative water content, osmotic potential, electrolyte leakage and malondialdehyde concentrations. Drought triggered changes in primary metabolism, especially increases in amino acids in both organs, but leaves and roots responded with different dynamics to rewatering. After a transient normalization of most metabolites within 8 days, a second accumulation of amino acids in leaves might indicate a stress imprint beneficial in upcoming drought events. Repair mechanisms seemed important during initial recovery and occurred at the expense of growth for at least 12 days. These results indicate that organ specific metabolic recovery responses might be related to distinct functions and concomitant disparate stress levels in above- and belowground organs. With respect to metabolism, recovery was not simply a reversal of the stress responses.

The study of plant metabolism impacts a broad range of domains such as plant cultural practices, plant breeding, human or animal nutrition, phytochemistry and green biotechnologies. Plant metabolites are extremely diverse in terms of structure or compound families as well as concentrations. This review attempts to illustrate how NMR spectroscopy, with its broad variety of experimental approaches, has contributed widely to the study of plant primary or specialized metabolism in very diverse ways. The review presents recent developments of one-dimensional and multi-dimensional NMR methods to study various aspects of plant metabolism. Through recent examples, it highlights how NMR has proved to be an invaluable tool for the global characterization of sample composition within metabolomic studies, and shows some examples of use for targeted phytochemistry, with a special focus on compound identification and quantitation. In such cases, NMR approaches are often used to provide snapshots of the plant sample composition. The review also covers dynamic aspects of metabolism, with a description of NMR techniques to measure metabolic fluxes - in most cases after stable isotope labelling. It is mainly intended for NMR specialists who would be interested to learn more about the potential of their favourite technique in plant sciences and about specific details of NMR approaches in this field. Therefore, as a practical guide, a paragraph on the specific precautions that should be taken for sample preparation is also included. In addition, since the quality of NMR metabolic studies is highly dependent on approaches to data processing and data sharing, a specific part is dedicated to these aspects. The review concludes with perspectives on the emerging methods that could change significantly the role of NMR in the field of plant metabolism by boosting its sensitivity. The review is illustrated throughout with examples of studies selected to represent diverse applications of liquid-state or HR-MAS NMR., (Copyright © 2017 Elsevier B.V. All rights reserved.)

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.

A detailed study of the diurnal compositional changes was performed in tomato (Solanum lycopersicum cv. Moneymaker) leaves and fruits. Plants were cultivated in a commercial greenhouse under two growth conditions: control and shaded. Expanding fruits and the closest mature leaves were harvested during two different day/night cycles (cloudy or sunny day). High-throughput robotized biochemical phenotyping of major compounds, as well as proton nuclear magnetic resonance and mass spectrometry metabolomic profiling, were used to measure the contents of about 70 metabolites in the leaves and 60 metabolites in the fruits, in parallel with ecophysiological measurements. Metabolite data were processed using multivariate, univariate, or clustering analyses and correlation networks. The shaded carbon-limited plants adjusted their leaf area, decreased their sink carbon demand and showed subtle compositional modifications. For source leaves, several metabolites varied along a diel cycle, including those directly linked to photosynthesis and photorespiration. These metabolites peaked at midday in both conditions and diel cycles as expected. However, transitory carbon storage was limited in tomato leaves. In fruits, fewer metabolites showed diel fluctuations, which were also of lower amplitude. Several organic acids were among the fluctuating metabolites. Diel patterns observed in leaves and especially in fruits differed between the cloudy and sunny days, and between the two conditions. Relationships between compositional changes in leaves and fruits are in agreement with the fact that several metabolic processes of the fruit appeared linked to its momentary supply of sucrose., (© The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

Cucumis melo fruit is highly valued for its sweet and refreshing flesh, however the flavour and value are also highly influenced by aroma as dictated by volatile organic compounds (VOCs). A simple and robust method of sampling VOCs on polydimethylsiloxane (PDMS) has been developed. Contrasting cultivars of C. melo subspecies melo were investigated at commercial maturity: three cultivars of var. Cantalupensis group Charentais (cv. Cézanne, Escrito, and Dalton) known to exhibit differences in ripening behaviour and shelf-life, as well as one cultivar of var. Cantalupensis group Ha'Ogan (cv. Noy Yisre'el) and one non-climacteric cultivar of var. Inodorus (cv. Tam Dew). The melon cultivar selection was based upon fruits exhibiting clear differences (cv. Noy Yisre'el and Tam Dew) and similarities (cv. Cézanne, Escrito, and Dalton) in flavour. In total, 58 VOCs were detected by thermal desorption (TD)-GC-MS which permitted the discrimination of each cultivar via Principal component analysis (PCA). PCA indicated a reduction in VOCs in the non-climacteric cv. Tam Dew compared to the four Cantalupensis cultivars. Within the group Charentais melons, the differences between the short, mid and long shelf-life cultivars were considerable. ¹H NMR analysis led to the quantification of 12 core amino acids, their levels were 3-10-fold greater in the Charentais melons, although they were reduced in the highly fragrant cv. Cézanne, indicating their role as VOC precursors. This study along with comparisons to more traditional labour intensive solid phase micro-extraction (SPME) GC-MS VOC profiling data has indicated that the high-throughput PDMS method is of great potential for the assessment of melon aroma and quality., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The spectra processing step is crucial in metabolomics approaches, especially for proton NMR metabolomics profiling. During this step, noise reduction, baseline correction, peak alignment and reduction of the 1D (1)H-NMR spectral data are required in order to allow biological information to be highlighted through further statistical analyses. Above all, data reduction (binning or bucketing) strongly impacts subsequent statistical data analysis and potential biomarker discovery. Here, we propose an efficient spectra processing method which also provides helpful support for compound identification using a new data reduction algorithm that produces relevant variables, called buckets. These buckets are the result of the extraction of all relevant peaks contained in the complex mixture spectra, rid of any non-significant signal. Taking advantage of the concentration variability of each compound in a series of samples and based on significant correlations that link these buckets together into clusters, the method further proposes automatic assignment of metabolites by matching these clusters with the spectra of reference compounds from the Human Metabolome Database or a home-made database. This new method is applied to a set of simulated (1)H-NMR spectra to determine the effect of some processing parameters and, as a proof of concept, to a tomato (1)H-NMR dataset to test its ability to recover the fruit extract compositions. The implementation code for both clustering and matching steps is available upon request to the corresponding author.

Background: Improvements in the techniques for metabolomics analyses and growing interest in metabolomic approaches are resulting in the generation of increasing numbers of metabolomic profiles. Platforms are required for profile management, as a function of experimental design, and for metabolite identification, to facilitate the mining of the corresponding data. Various databases have been created, including organism-specific knowledgebases and analytical technique-specific spectral databases. However, there is currently no platform meeting the requirements for both profile management and metabolite identification for nuclear magnetic resonance (NMR) experiments., Description: MeRy-B, the first platform for plant (1)H-NMR metabolomic profiles, is designed (i) to provide a knowledgebase of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata, (ii) for queries and visualization of the data, (iii) to discriminate between profiles with spectrum visualization tools and statistical analysis, (iv) to facilitate compound identification. It contains lists of plant metabolites and unknown compounds, with information about experimental conditions, the factors studied and metabolite concentrations for several plant species, compiled from more than one thousand annotated NMR profiles for various organs or tissues., Conclusion: MeRy-B manages all the data generated by NMR-based plant metabolomics experiments, from description of the biological source to identification of the metabolites and determinations of their concentrations. It is the first database allowing the display and overlay of NMR metabolomic profiles selected through queries on data or metadata. MeRy-B is available from http://www.cbib.u-bordeaux2.fr/MERYB/index.php.

• Variations in tissue development and spatial composition have a major impact on the nutritional and organoleptic qualities of ripe fleshy fruit, including melon (Cucumis melo). To gain a deeper insight into the mechanisms involved in these changes, we identified key metabolites for rational food quality design. • The metabolome, volatiles and mineral elements were profiled employing an unprecedented range of complementary analytical technologies. Fruits were followed at a number of time points during the final ripening process and tissues were collected across the fruit flesh from rind to seed cavity. Approximately 2000 metabolite signatures and 15 mineral elements were determined in an assessment of temporal and spatial melon fruit development. • This study design enabled the identification of: coregulated hubs (including aspartic acid, 2-isopropylmalic acid, β-carotene, phytoene and dihydropseudoionone) in metabolic association networks; global patterns of coordinated compositional changes; and links of primary and secondary metabolism to key mineral and volatile fruit complements. • The results reveal the extent of metabolic interactions relevant to ripe fruit quality and thus have enabled the identification of essential candidate metabolites for the high-throughput screening of melon breeding populations for targeted breeding programmes aimed at nutrition and flavour improvement., (© 2011 The Authors. New Phytologist © 2011 New Phytologist Trust.)

A metabolomics approach combining (1)H NMR and gas chromatography-electrospray ionization time-of-flight mass spectrometry (GC-EI-TOFMS) profiling was employed to characterize melon (Cucumis melo L.) fruit. In a first step, quantitative (1)H NMR of polar extracts and principal component analyses (PCA) of the corresponding data highlighted the major metabolites in fruit flesh, including sugars, organic acids, and amino acids. In a second step, the spatial localization of metabolites was investigated using both analytical techniques. Direct (1)H NMR profiling of juice or GC-EI-TOFMS profiling of tissue extracts collected from different locations in the fruit flesh provided information on advantages and drawbacks of each technique for the analysis of a sugar-rich matrix such as fruit. (1)H NMR and GC-EI-TOFMS data sets were compared using independently performed PCA and multiblock hierarchical PCA (HPCA), respectively. In addition a correlation-based multiblock HPCA was used for direct comparison of both analytical data sets. These data analyses revealed several gradients of metabolites in fruit flesh which can be related with differences in metabolism and indicated the suitability of multiblock HPCA for correlation of data from two (or potentially more) metabolomics platforms.

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. Metabolomic and proteomic responses of diverse maize hybrids to progressive decreasing temperatures were larger from 20 to 16°C, partly mimicked those in the field, and involved primary and specialized metabolisms. [ABSTRACT FROM AUTHOR]

The long-term effect of a plant (P)-based diet was assessed by proton nuclear magnetic resonance (1H-NMR) metabolomics in rainbow trout fed a marine fish meal (FM)–fish oil (FO) diet (M), a P-based diet and a control commercial-like diet (C) starting with the first feeding. Growth performances were not heavily altered by long-term feeding on the P-based diet. An 1H-NMR metabolomic analysis of the feed revealed significantly different soluble chemical compound profiles between the diets. A set of soluble chemical compounds was found to be specific either to the P-based diet or to the M diet. Pterin, a biomarker of plant feedstuffs, was identified both in the P-based diet and in the plasma of fish fed the P-based diet. 1H-NMR metabolomic analysis on fish plasma and liver and muscle tissues at 6 and 48 h post feeding revealed significantly different profiles between the P-based diet and the M diet, while the C diet showed intermediate results. A higher amino acid content was found in the plasma of fish fed the P-based diet compared with the M diet after 48 h, suggesting either a delayed delivery of the amino acids or a lower amino acid utilisation in the P-based diet. This was associated with an accumulation of essential amino acids and the depletion of glutamine in the muscle, together with an accumulation of choline in the liver. Combined with an anticipated absorption of methionine and lysine supplemented in free form, the present results suggest an imbalanced essential amino acid supply for protein metabolism in the muscle and for specific functions of the liver. [ABSTRACT FROM AUTHOR]

Aquaculture is facing a strategic challenge to improve feed suitability and support the global increase in fish production. Improvements in diet formulation for sustainable nutritional strategies have focused to date on the partial substitution of marine resources by plant resources but will now include other alternative feedstuffs. Growth trials and body composition data provide valuable indicators of fish nutritional status, while omics technologies may contribute to a better understanding of fish nutrition and help to demonstrate how feed and nutrients act in fish metabolism. Metabolomic approaches give an insight into fish metabolism through a non‐targeted analysis of metabolites in tissues or biofluids that involve multiple factors affecting fish, such as nutrition. In this review, we highlight the outcomes of publications in metabolomics applied to fish nutrition. We explain the concept of metabolomics and discuss specific technical considerations related to sample type, sampling and sample preparation. We show how metabolomic studies help to elucidate the impact of nutrition on fish fillet composition and fish metabolism. Finally, we describe the potential applications of metabolomic approaches for the non‐invasive monitoring of fish nutritional status. [ABSTRACT FROM AUTHOR]

Yield formation in regions with intermittent drought periods depends on the plant’s ability to recover after cessation of the stress. The present work assessed differences in metabolic recovery of leaves and roots of drought-stressed sugar beets with high temporal resolution. Plants were subjected to drought for 13 days, and rewatered for 12 days. At one to two-day intervals, plant material was harvested for untargeted 1H-NMR metabolomic profiling, targeted analyses of hexose-phosphates, starch, amino acids, nitrate and proteins, and physiological measurements including relative water content, osmotic potential, electrolyte leakage and malondialdehyde concentrations. Drought triggered changes in primary metabolism, especially increases in amino acids in both organs, but leaves and roots responded with different dynamics to rewatering. After a transient normalization of most metabolites within 8 days, a second accumulation of amino acids in leaves might indicate a stress imprint beneficial in upcoming drought events. Repair mechanisms seemed important during initial recovery and occurred at the expense of growth for at least 12 days. These results indicate that organ specific metabolic recovery responses might be related to distinct functions and concomitant disparate stress levels in above- and belowground organs. With respect to metabolism, recovery was not simply a reversal of the stress responses. [ABSTRACT FROM AUTHOR]

The spectra processing step is crucial in metabolomics approaches, especially for proton NMR metabolomics profiling. During this step, noise reduction, baseline correction, peak alignment and reduction of the 1D H-NMR spectral data are required in order to allow biological information to be highlighted through further statistical analyses. Above all, data reduction (binning or bucketing) strongly impacts subsequent statistical data analysis and potential biomarker discovery. Here, we propose an efficient spectra processing method which also provides helpful support for compound identification using a new data reduction algorithm that produces relevant variables, called buckets. These buckets are the result of the extraction of all relevant peaks contained in the complex mixture spectra, rid of any non-significant signal. Taking advantage of the concentration variability of each compound in a series of samples and based on significant correlations that link these buckets together into clusters, the method further proposes automatic assignment of metabolites by matching these clusters with the spectra of reference compounds from the Human Metabolome Database or a home-made database. This new method is applied to a set of simulated H-NMR spectra to determine the effect of some processing parameters and, as a proof of concept, to a tomato H-NMR dataset to test its ability to recover the fruit extract compositions. The implementation code for both clustering and matching steps is available upon request to the corresponding author. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Drought stress is one of the major environmental factors responsible for yield and quality losses in sugar beet production. In view of a predicted increase in early season drought periods, the ability of the plants to recover from a stress event will become increasingly important for sustained yield. The present study aimed at the identification and characterization of major metabolites of the primary metabolism to uncover leaf- and root-specific metabolic recovery of transiently drought-stressed sugar beets. We integrated a metabolomic strategy, non-targeted proton nuclear magnetic resonance spectroscopy (1H NMR), targeted enzyme-based metabolite assays, and physiological measurements to identify crucial components of the metabolic response [1]. Sugar beet cultivar Pauletta was grown under controlled conditions at 24°C day / 18°C night, 75±10% relative humidity and a photoperiod of 16 h light (>250 μmol m2 s-1). When 4-5 leaves were visible, plants were subjected to drought for 13 days followed by gradual rewatering for 12 days. Control plants were kept well-watered throughout the experiment. At one to two-day intervals during drought and recovery, the youngest fully expanded leaf pair (YEL) and the root part 1.5 cm below the crown were harvested 2 h after the onset of the photoperiod. Materials were immediately frozen in liquid nitrogen, lyophilised and stored at -80°C until analysis Drought triggered changes in primary metabolism, especially increases in amino acid levels in both organs, accumulation of compatible solutes such as proline and glycine betaine in leaves, and of raffinose and glucose in roots. Upon rewatering, leaves and roots responded with different dynamics. While most metabolites returned to control levels within 5 days in leaves, amino acids recovered more slowly, but consistently in roots. Surprisingly, a second accumulation of amino acids and a strong increase in starch was observed after 8 days of recovery in leaves, while at the same time serine accumulated in roots. Both effects might indicate a stress imprint beneficial in upcoming drought events. With respect to metabolism, drought and recovery are two distinct processes subject to different regulatory mechanisms actively driven by the plant. Organ specific metabolic recovery responses might be related to distinct functions and concomitant disparate stress levels in above- and belowground organs. [ABSTRACT FROM AUTHOR]

The article provides information on the use of nuclear magnetic resonance for plant metabolomics and spectra processing for plant development. Topics include separation techniques coupled with mass spectrometry, metabolic fingerprinting of plants and interactions between biologists and spectroscopists for metabolite identification.

Over the past 10 years, knowledge about several aspects of fruit metabolism has been greatly improved. Notably, high-throughput metabolomic technologies have allowed quantifying metabolite levels across various biological processes, and identifying the genes that underly fruit development and ripening. This Special Issue is designed to exemplify the current use of metabolomics studies of temperate and tropical fruit for basic research as well as practical applications. It includes articles about different aspects of fruit biochemical phenotyping, fruit metabolism before and after harvest, including primary and specialized metabolisms, and bioactive compounds involved in growth and environmental responses. The effect of genotype, stages of development or fruit tissue on metabolomic profiles and corresponding metabolism regulations are addressed, as well as the combination of other omics with metabolomics for fruit metabolism studies. [ABSTRACT FROM AUTHOR]

The broad variability of Cucumis melo (melon, Cucurbitaceae) presents a challenge to conventional classification and organization within the species. To shed further light on the infraspecific relationships within C. melo, we compared genotypic and metabolomic similarities among 44 accessions representative of most of the cultivar-groups. Genotyping-by-sequencing (GBS) provided over 20,000 single-nucleotide polymorphisms (SNPs). Metabolomics data of the mature fruit flesh and rind provided over 80,000 metabolomic and elemental features via an orchestra of six complementary metabolomic platforms. These technologies probed polar, semi-polar, and non-polar metabolite fractions as well as a set of mineral elements and included both flavor- and taste-relevant volatile and non-volatile metabolites. Together these results enabled an estimate of "metabolomic/elemental distance" and its correlation with the genetic GBS distance of melon accessions. This study indicates that extensive and non-targeted metabolomics/elemental characterization produced classifications that strongly, but not completely, reflect the current and extensive genetic classification. Certain melon Groups, such as Inodorous, clustered in parallel with the genetic classifications while other genome to metabolome/element associations proved less clear. We suggest that the combined genomic, metabolic, and element data reflect the extensive sexual compatibility among melon accessions and the breeding history that has, for example, targeted metabolic quality traits, such as taste and flavor. [ABSTRACT FROM AUTHOR]

Nutrition of high trophic species in aquaculture is faced with the development of sustainable plant-based diets. Insects seem particularly promising for supplementing plant-based diets. However, the complex effect of whole insect meal on fish metabolism is not well understood, and even less is known about insect meal extracts. The purpose of this work was to decipher the metabolic utilization of a plant-based diet supplemented with the gradual addition of an insect protein extract (insect hydrolysate at 0%, 5%, 10% and 15%). 1H-NMR profiling was used to assess metabolites in experimental diets and in fish plasma, liver and muscle. A significant dose-dependent increase in growth and feed efficiency with increasing insect extract amounts was observed. The incremental incorporation of the insect extract in diet had a significant and progressive impact on the profile of dietary soluble compounds and trout metabolome. The metabolites modulated by dietary insect extracts in plasma and tissues were involved in protein and energy metabolism. This was associated with the efficient metabolic use of dietary free amino acids toward protein synthesis through the concomitant supply of balanced free amino acids and energy substrates in muscle. The findings provide new insights into how the dietary food metabolome affects fish metabolism. [ABSTRACT FROM AUTHOR]

Fruit is a complex organ containing seeds and several interconnected tissues with dedicated roles. However, most biochemical or molecular studies about fleshy fruit development concern the entire fruit, the fruit without seeds, or pericarp only. We studied tomato (Solanum lycopersicum) fruit at four stages of development (12, 20, 35, and 45 days post-anthesis). We separated the seeds and the other tissues, exocarp, mesocarp, columella with placenta and locular tissue, and analyzed them individually using proton NMR metabolomic profiling for the quantification of major polar metabolites, enzymatic analysis of starch, and LC-DAD analysis of isoprenoids. Pericarp tissue represented about half of the entire fruit mass only. The composition of each fruit tissue changed during fruit development. An ANOVA-PCA highlighted common, and specific metabolite trends between tissues e.g., higher contents of chlorogenate in locular tissue and of starch in columella. Euclidian distances based on compositional data showed proximities within and between tissues. Several metabolic regulations differed between tissues as revealed by the comparison of metabolite networks based on correlations between compounds. This work stressed the role of specific tissues less studied than pericarp but that impact fruit organoleptic quality including its shape and taste, and fruit processing quality. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]