Applications of NMR metabolomics to the study of foodstuffs: truffle, kiwifruit, lettuce, and sea bass

Italian White Truffle (Tuber magnatum Pico): Discovery of new molecules through untargeted UHPLC-QTOF-MS analysis

The Italian white truffle (Tuber magnatum Pico) is worldwide recognized as one of the most expensive edible mushrooms. Its chemical characterization has not yet been properly investigated in scientific literature. The aim of this study was to explore, for the first time, the truffle polar metabolic profile using an untargeted approach through UHPLC-ESI-QTOF-MS data-dependent acquisition. The total features list was filtered and molecules were annotated according to the MS spectra correspondence score with a threshold of 60 %. This led to a total of 412 annotated compounds mainly referred to amino acids, B-vitamins, carbohydrates and fatty acids derivatives. A targeted analysis was applied to four annotated molecules never detected in truffle before, being riboflavin, azelaic, 2-isopropylmalic and 3-isopropylmalic acids. Some constituents of the extracts were semi-quantitatively analysed by 1H NMR spectroscopy. Results place a first brick in white truffle characterization, paving the way towards authenticity biomarkers detection useful in frauds prevention.

Comparative metabolomic in-depth exploration of red raspberry: new insights into changes in phytochemicals between different breeds

Based on a non-targeted metabolomic approach, a comprehensive analysis of the metabolic profiles of two raspberry cultivars, Selina (TSM) and Tulameen (CSM), was conducted to explore the potential for further processing of these two varieties. A total of 752 metabolites were identified in both raspberry varieties, with 375 metabolites detected in negative ion mode and additional metabolites identified in positive ion mode. The total number of differential metabolites between TSM and CSM was 62, with orthogonal partial least squares discriminant analysis (OPLS-DA) revealing that the main differential metabolites between the two varieties were phenolic compounds, organic acids, and alkaloids. KEGG pathway analysis identified the top three significantly different metabolic pathways as biosynthesis of amino acids; valine, leucine, and isoleucine biosynthesis; and alanine, aspartate, and glutamate metabolism. In conclusion, this study comprehensively analyzed the metabolic characteristics of TSM and CSM raspberry varieties, providing valuable insights and revealing their potential application prospects. Compared to previous studies, this research provides new insights into the metabolic differences between TSM and CSM cultivars, specifically highlighting newly identified metabolites that were not reported before. These findings include novel differences in phenolic compounds and alkaloids, which play important roles in plant stress response and have potential health benefits. This enhances our understanding of the unique properties of each cultivar and underscores the biological functions of the newly identified metabolites, contributing to the broader field of functional food development.

Mapping taste and flavour traits to genetic markers in lettuce Lactuca sativa

Lettuce is the most highly consumed raw leafy vegetable crop eaten worldwide, making it nutritionally important in spite of its comparatively low nutrient density in relation to other vegetables. However, the perception of bitterness caused by high levels of sesquiterpenoid lactones and comparatively low levels of sweet tasting sugars limits palatability. To assess variation in nutritional and taste-related metabolites we assessed 104 members of a Lactuca sativa cv. Salinas x L. serriola (accession UC96US23) mapping population. Plants were grown in three distinct environments, and untargeted NMR and HPLC were used as a rapid chemotyping method, from which 63 unique Quantitative Trait Loci (QTL) were identified. We were able to identify putative regulatory candidate genes underlying the QTL for fructose on linkage group 9, which accounted for up to 36 % of our population variation, and which was stable across all three growing environments; and for 15-p-hydroxyyphenylacetyllactucin-8-sulfate on linkage group 5 which has previously been identified for its low bitterness, while retaining anti-herbivory field effects. We also identified a candidate gene for flavonoid 3',5'- hydroxylase underlying a polyphenol QTL on linkage group 5, and two further candidate genes in sugar biosynthesis on linkage groups 2 and 5. Collectively these candidate genes and their associated markers can inform a route for plant breeders to improve the palatability and nutritional value of lettuce in their breeding programmes.

NMR Metabolomics of Arctium lappa L., Taraxacum officinale and Melissa officinalis: A Comparison of Spontaneous and Organic Ecotypes

Officinal plants are a source of metabolites whose chemical composition depends on pedoclimatic conditions. In this study, the NMR-based approach was applied to investigate the impacts of different altitudes and agronomical practices (Land, Mountain Spontaneous, and Organically Grown Ecotypes, namely LSE, MSE, and OE, respectively) on the metabolite profiles of Burdock root, Dandelion root and aerial part, and Lemon balm aerial part. Sugars, amino acids, organic acids, polyphenols, fatty acids, and other metabolites were identified and quantified in all samples. Some metabolites turned out to be tissue-specific markers. Arginine was found in roots, whereas myo-inositol, galactose, glyceroyldigalactose moiety, pheophytin, and chlorophyll were identified in aerial parts. Caftaric and chicoric acids, 3,5 di-caffeoylquinic acid, and chlorogenic and rosmarinic acids were detected in Dandelion, Burdock and Lemon balm, respectively. The metabolite amount changed significantly according to crop, tissue type, and ecotype. All ecotypes of Burdock had the highest contents of amino acids and the lowest contents of organic acids, whereas an opposite trend was observed in Lemon balm. Dandelion parts contained high levels of carbohydrates, except for the MSE aerial part, which showed the highest content of organic acids. The results provided insights into the chemistry of officinal plants, thus supporting nutraceutical-phytopharmaceutical research.

Comprehensive metabolite and biological profile of "Sulmona Red Garlic" ecotype's aerial bulbils

"Sulmona Red Garlic" is a well-known Italian traditional product. Bulbs, used for culinary purposes, have been largely investigated for their medicinal properties whereas aerial bulbils are usually removed as waste material. Here, for the first time, chemical composition and biological properties of the hydroalcoholic extract from aerial bulbils were investigated. Complementary information on metabolite composition were obtained using both NMR based untargeted and HPLC-DAD targeted methodologies. The NMR analysis revealed the presence of sugars, organic acids, amino acids, organosulphur compounds (methiin, alliin, allicin and cycloalliin), and other secondary metabolites. In particular, methiin and alliin were identified for the first time in the NMR spectra of aerial bulbil garlic extracts. Polyphenol content was determined by HPLC-DAD analysis: catechin, chlorogenic acid, and gallic acid turned out to be the most abundant phenolics. Hydroalcoholic extract blocked cell proliferation of colon cancer cell line HCT116 with an IC50 of 352.07 µg/mL, while it was non-toxic to myoblast cell line C2C12. In addition, it caused seedling germination reduction of two edible and herbaceous dicotyledon species, namely Cichorium intybus and C. endivia. Moreover, the same extract reduced the gene expression of TNF-α (tumor necrosis factor), HIF1-α (hypoxia-inducible factor), VEGFA (vascular endothelial growth factor), and transient receptor potential (TRP) M8 (TRPM8) indicating the ability to contrast cancer development through the angiogenic pathway. Final, in silico experiments were also carried out supporting the biological effects of organosulphur compounds, particularly alliin, which may directly interact with TRPM8. The results here reported suggest the potential use of garlic aerial bulbils often considered a waste product as a source in phytotherapeutic remedies.

From Nontargeted to Targeted Analysis: Feature Selection in the Differentiation of Truffle Species (Tuber spp.) Using 1H NMR Spectroscopy and Support Vector Machine

The price of different truffle types varies according to their culinary value, sometimes by more than a factor of 10. Nonprofessionals can hardly distinguish visually the species within the white or black truffles, making the possibility of food fraud very easy. Therefore, the identification of different truffle species (Tuber spp.) is an analytical task that could be solved in this study. The polar extract from a total of 80 truffle samples was analyzed by 1H NMR spectroscopy in combination with chemometric methods covering five commercially relevant species. All classification models were validated applying a repeated nested cross-validation. In direct comparison, the two very similar looking and closely related black representatives Tuber melanosporum and Tuber indicum could be classified 100% correctly. The most expensive truffle Tuber magnatum could be distinguished 100% from the other relevant white truffle Tuber borchii. In addition, signals for a potential Tuber borchii and a potential Tuber melanosporum marker for targeted approaches could be detected, and the corresponding molecules were identified as betaine and ribonate. A model covering all five truffle species Tuber aestivum, Tuber borchii, Tuber indicum, Tuber magnatum, and Tuber melanosporum was able to correctly discriminate between each of the species.

Opening the Random Forest Black Box of 1H NMR Metabolomics Data by the Exploitation of Surrogate Variables

The untargeted metabolomics analysis of biological samples with nuclear magnetic resonance (NMR) provides highly complex data containing various signals from different molecules. To use these data for classification, e.g., in the context of food authentication, machine learning methods are used. These methods are usually applied as a black box, which means that no information about the complex relationships between the variables and the outcome is obtained. In this study, we show that the random forest-based approach surrogate minimal depth (SMD) can be applied for a comprehensive analysis of class-specific differences by selecting relevant variables and analyzing their mutual impact on the classification model of different truffle species. SMD allows the assignment of variables from the same metabolites as well as the detection of interactions between different metabolites that can be attributed to known biological relationships.

Analyses of serum and urinary metabolites in individuals with peripheral artery disease (PAD) consuming a bean-rich diet: Relationships with drug metabolites

Peripheral artery disease (PAD) has high morbidity and mortality rates. A metabolomics approach was employed to determine whether consumption of bean-rich diets for 8 weeks would impact the metabolomic profile of PAD individuals. Serum and urine, collected from 54 participants with clinical PAD at baseline and after 8 weeks on 0.3 cups beans/d (n=19), 0.6 cups beans/d (n= 20), or control (n=23) diet, and the beans were extracted and analyzed using LC-QTOF-MS. As a result, PGE2 p-acetamidophenyl ester, PGF2α diethyl amide and 5-L-glutamyl-L-alanine were significantly changed in the serum or urine of bean groups compared to control. Significant changes (P<0.05) in the profile and/or levels of 22 flavonoids present in bean extracts showed the potential importance of the mixture of beans used in this study. In a subset of participants taking metoprolol, after 8 weeks the bean-rich diets significantly elevated metoprolol in the serum while reducing it in urine compared to baseline. In addition, the diets significantly enhanced the urinary excretion of metformin. In conclusion, several biochemical pathways including prostaglandins and glutathione were affected by bean consumption. Significant changes in the metabolism of metoprolol and metformin with bean consumption suggested the presence of diet-drug interactions that may require adjustment of the prescribed dose. ClinicalTrials.gov Identifier: NCT01382056 Novelty: • Bean consumption by people with PAD alters the levels of certain metabolites in serum and urine • Different bean types (black, red kidney, pinto, navy) have unique flavonoid profiles • Metabolomics revealed potential diet-dug interactions as serum and/or urinary levels of metoprolol and metformin are modified by bean consumption.

The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science

The environment, from microbial ecosystems to recycled resources, fluctuates dynamically due to many physical, chemical and biological factors, the profile of which reflects changes in overall state, such as environmental illness caused by a collapse of homeostasis. To evaluate and predict environmental health in terms of systemic homeostasis and resource balance, a comprehensive understanding of these factors requires an approach based on the "exposome paradigm", namely the totality of exposure to all substances. Furthermore, in considering sustainable development to meet global population growth, it is important to gain an understanding of both the circulation of biological resources and waste recycling in human society. From this perspective, natural environment, agriculture, aquaculture, wastewater treatment in industry, biomass degradation and biodegradable materials design are at the forefront of current research. In this respect, nuclear magnetic resonance (NMR) offers tremendous advantages in the analysis of samples of molecular complexity, such as crude bio-extracts, intact cells and tissues, fibres, foods, feeds, fertilizers and environmental samples. Here we outline examples to promote an understanding of recent applications of solution-state, solid-state, time-domain NMR and magnetic resonance imaging (MRI) to the complex evaluation of organisms, materials and the environment. We also describe useful databases and informatics tools, as well as machine learning techniques for NMR analysis, demonstrating that NMR data science can be used to evaluate the exposome in both the natural environment and human society towards a sustainable future.

NMR-Based Plant Metabolomics in Nutraceutical Research: An Overview

Few topics are able to channel the interest of researchers, the public, and industries, like nutraceuticals. The ever-increasing demand of new compounds or new sources of known active compounds, along with the need of a better knowledge about their effectiveness, mode of action, safety, etc., led to a significant effort towards the development of analytical approaches able to answer the many questions related to this topic. Therefore, the application of cutting edges approaches to this area has been observed. Among these approaches, metabolomics is a key player. Herewith, the applications of NMR-based metabolomics to nutraceutical research are discussed: after a brief overview of the analytical workflow, the use of NMR-based metabolomics to the search for new compounds or new sources of known nutraceuticals are reviewed. Then, possible applications for quality control and nutraceutical optimization are suggested. Finally, the use of NMR-based metabolomics to study the impact of nutraceuticals on human metabolism is discussed.

LC-MS-Based Metabolomic Approach Revealed the Significantly Different Metabolic Profiles of Five Commercial Truffle Species

Truffles are ascomycetous ectomycorrhizal fungi that have elevated status in the culinary field due to their unique aroma and taste as well as their nutritional value and potential biological activities. Tuber melanosporum, T. indicum, T. panzhihuanense, T. sinoaestivum, and T. pseudoexcavatum are five commercial truffle species mainly distributed in Europe or China. In this study, an untargeted metabolomics technology based on an ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was applied to analyze the metabolic profiles and variations among these five truffle species. In our results, a total of 2376 metabolites were identified under positive ion mode, of which 1282 had significantly differential amounts and covered 110 pathways or metabolisms. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) revealed a clear separation from each of these five truffles, indicating a significantly different metabolic profile among them, with the biggest difference between T. melanosporum and the other four truffles. The differential metabolites covered various chemical categories, and a detailed analysis was performed for nine metabolic categories, including amino acids, saccharides and nucleosides, organic acids, alkaloids, flavonoids, carnitines, phenols and alcohols, esters, and sulfur compounds. For each of the nine categories, most of metabolites predominantly accumulated in T. melanosporum compared with the other four truffles. Meanwhile, there were significant differences of the average ion intensity in each category among the five truffles, e.g., higher amounts of amino acids was detected in T. panzhihuanense and T. pseudoexcavatum; T. indicum contained significantly more carnitines, while there were more alkaloids in T. melanosporum. Additionally, some metabolites with biological activities were discussed for each category, such as acetyl-L-carnitine, adenine, neobavaisoflavone, and anandamide. Generally, this study may provide the valuable information regarding the variation of the metabolic composition of these five commercial truffle species, and the biological significance of these metabolites was uncovered to explore the metabolic mechanisms of truffles, which would be helpful for further research on the compounds and potential biological functions in truffles that have not yet been investigated.

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.

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.

Photosystem-II D1 protein mutants of Chlamydomonas reinhardtii in relation to metabolic rewiring and remodelling of H-bond network at QB site

Photosystem II (PSII) reaction centre D1 protein of oxygenic phototrophs is pivotal for sustaining photosynthesis. Also, it is targeted by herbicides and herbicide-resistant weeds harbour single amino acid substitutions in D1. Conservation of D1 primary structure is seminal in the photosynthetic performance in many diverse species. In this study, we analysed built-in and environmentally-induced (high temperature and high photon fluency – HT/HL) phenotypes of two D1 mutants of Chlamydomonas reinhardtii with Ala250Arg (A250R) and Ser264Lys (S264K) substitutions. Both mutations differentially affected efficiency of electron transport and oxygen production. In addition, targeted metabolomics revealed that the mutants undergo specific differences in primary and secondary metabolism, namely, amino acids, organic acids, pigments, NAD, xanthophylls and carotenes. Levels of lutein, β-carotene and zeaxanthin were in sync with their corresponding gene transcripts in response to HT/HL stress treatment in the parental (IL) and A250R strains. D1 structure analysis indicated that, among other effects, remodelling of H-bond network at the Q_B site might underpin the observed phenotypes. Thus, the D1 protein, in addition to being pivotal for efficient photosynthesis, may have a moonlighting role in rewiring of specific metabolic pathways, possibly involving retrograde signalling.

A multi-methodological approach in the study of Italian PDO "Cornetto di Pontecorvo" red sweet pepper

A multi-methodological approach was applied to study red sweet peppers (Capsicum annuum L.) ecotype "Cornetto di Pontecorvo" grown in a greenhouse or in open field. This approach includes morphological analysis, chemical composition determination, and biological activity evaluation of different extracts from pepper fruits. Untargeted analyses, namely NMR spectroscopy and mass spectrometry, allowed the comprehensive pepper metabolite profile of pepper pulp, peel and seeds hydroalcoholic and organic extracts to be determined, showing the presence of sugars, organic acids, amino acids and other secondary metabolites. Targeted analyses, such as HPLC-PDA, HPLC-TLC and spectrophotometric analyses allowed polyphenols, tannins, flavonoids and pigments content to be determined. Samples quality and freshness were verified by the low content of biogenic amines and mycotoxins, as determined using HPLC-FLD and HPLC-MS, respectively. Preliminary biological results demonstrated the ability of the organic extracts to inhibit α-amylase, a key enzyme in the control of glucose metabolism.

¹H NMR and Multivariate Analysis for Geographic Characterization of Commercial Extra Virgin Olive Oil: A Possible Correlation with Climate Data

¹H Nuclear Magnetic Resonance (NMR) spectroscopy coupled with multivariate analysis has been applied in order to investigate metabolomic profiles of more than 200 extravirgin olive oils (EVOOs) collected in a period of over four years (2009-2012) from different geographic areas. In particular, commercially blended EVOO samples originating from different Italian regions (Tuscany, Sicily and Apulia), as well as European (Spain and Portugal) and non-European (Tunisia, Turkey, Chile and Australia) countries. Multivariate statistical analysis (Principal Component Analisys (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA)) applied on the NMR data revealed the existence of marked differences between Italian (in particular from Tuscany, Sicily and Apulia regions) and foreign (in particular Tunisian) EVOO samples. A possible correlation with available climate data has been also investigated. These results aim to develop a powerful NMR-based tool able to protect Italian olive oil productions.

FoodPro: A Web-Based Tool for Evaluating Covariance and Correlation NMR Spectra Associated with Food Processes

Foods from agriculture and fishery products are processed using various technologies. Molecular mixture analysis during food processing has the potential to help us understand the molecular mechanisms involved, thus enabling better cooking of the analyzed foods. To date, there has been no web-based tool focusing on accumulating Nuclear Magnetic Resonance (NMR) spectra from various types of food processing. Therefore, we have developed a novel web-based tool, FoodPro, that includes a food NMR spectrum database and computes covariance and correlation spectra to tasting and hardness. As a result, FoodPro has accumulated 236 aqueous (extracted in D₂O) and 131 hydrophobic (extracted in CDCl₃) experimental bench-top 60-MHz NMR spectra, 1753 tastings scored by volunteers, and 139 hardness measurements recorded by a penetrometer, all placed into a core database. The database content was roughly classified into fish and vegetable groups from the viewpoint of different spectrum patterns. FoodPro can query a user food NMR spectrum, search similar NMR spectra with a specified similarity threshold, and then compute estimated tasting and hardness, covariance, and correlation spectra to tasting and hardness. Querying fish spectra exemplified specific covariance spectra to tasting and hardness, giving positive covariance for tasting at 1.31 ppm for lactate and 3.47 ppm for glucose and a positive covariance for hardness at 3.26 ppm for trimethylamine N-oxide.

Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine

"Omics" sciences have been developed to provide a holistic point of view of biology and to better understand the complexity of an organism as a whole. These systems biology approaches can be examined at different levels, starting from the most fundamental, i.e., the genome, and finishing with the most functional, i.e., the metabolome. Similar to how genomics is applied to the exploration of DNA, metabolomics is the qualitative and quantitative study of metabolites. This emerging field is clearly linked to genomics, transcriptomics, and proteomics. In addition, metabolomics provides a unique and direct vision of the functional outcome of an organism's activities that are required for it to survive, grow, and respond to internal and external stimuli or stress, e.g., pathologies and drugs. The links between metabolic changes, patient phenotype, physiological and/or pathological status, and treatment are now well established and have opened a new area for the application of metabolomics in the drug discovery process and in personalized medicine.

Metabolomics by Proton High-Resolution Magic-Angle-Spinning Nuclear Magnetic Resonance of Tomato Plants Treated with Two Secondary Metabolites Isolated from Trichoderma

Trichoderma fungi release 6-pentyl-2H-pyran-2-one (1) and harzianic acid (2) secondary metabolites to improve plant growth and health protection. We isolated metabolites 1 and 2 from Trichoderma strains, whose different concentrations were used to treat seeds of Solanum lycopersicum. The metabolic profile in the resulting 15 day old tomato leaves was studied by high-resolution magic-angle-spinning nuclear magnetic resonance (HRMAS NMR) spectroscopy directly on the whole samples without any preliminary extraction. Principal component analysis (PCA) of HRMAS NMR showed significantly enhanced acetylcholine and γ-aminobutyric acid (GABA) content accompanied by variable amount of amino acids in samples treated with both Trichoderma secondary metabolites. Seed germination rates, seedling fresh weight, and the metabolome of tomato leaves were also dependent upon doses of metabolites 1 and 2 treatments. HRMAS NMR spectroscopy was proven to represent a rapid and reliable technique for evaluating specific changes in the metabolome of plant leaves and calibrating the best concentration of bioactive compounds required to stimulate plant growth.

Beneficial mycorrhizal symbionts affecting the production of health-promoting phytochemicals

Fresh fruits and vegetables are largely investigated for their content in vitamins, mineral nutrients, dietary fibers, and plant secondary metabolites, collectively called phytochemicals, which play a beneficial role in human health. Quantity and quality of phytochemicals may be detected by using different analytical techniques, providing accurate quantification and identification of single molecules, along with their molecular structures, and allowing metabolome analyses of plant-based foods. Phytochemicals concentration and profiles are affected by biotic and abiotic factors linked to plant genotype, crop management, harvest season, soil quality, available nutrients, light, and water. Soil health and biological fertility play a key role in the production of safe plant foods, as a result of the action of beneficial soil microorganisms, in particular of the root symbionts arbuscular mycorrhizal fungi. They improve plant nutrition and health and induce changes in secondary metabolism leading to enhanced biosynthesis of health-promoting phytochemicals, such as polyphenols, carotenoids, flavonoids, phytoestrogens, and to a higher activity of antioxidant enzymes. In this review we discuss reports on health-promoting phytochemicals and analytical methods used for their identification and quantification in plants, and on arbuscular mycorrhizal fungi impact on fruits and vegetables nutritional and nutraceutical value.

Influence of Freezing and Storage Procedure on Human Urine Samples in NMR-Based Metabolomics

It is consensus in the metabolomics community that standardized protocols should be followed for sample handling, storage and analysis, as it is of utmost importance to maintain constant measurement conditions to identify subtle biological differences. The aim of this work, therefore, was to systematically investigate the influence of freezing procedures and storage temperatures and their effect on NMR spectra as a potentially disturbing aspect for NMR-based metabolomics studies. Urine samples were collected from two healthy volunteers, centrifuged and divided into aliquots. Urine aliquots were frozen either at -20 °C, on dry ice, at -80 °C or in liquid nitrogen and then stored at -20 °C, -80 °C or in liquid nitrogen vapor phase for 1-5 weeks before NMR analysis. Results show spectral changes depending on the freezing procedure, with samples frozen on dry ice showing the largest deviations. The effect was found to be based on pH differences, which were caused by variations in CO2 concentrations introduced by the freezing procedure. Thus, we recommend that urine samples should be frozen at -20 °C and transferred to lower storage temperatures within one week and that freezing procedures should be part of the publication protocol.

Metabolic profiling and outer pericarp water state in Zespri, CI.GI, and Hayward kiwifruits

The metabolic profiling of aqueous extracts of Zespri Gold ( Actinidia chinensis ) and CI.GI (a controlled crossbreed from different species of Actinidia deliciosa ) kiwifruits and the water state of the outer pericarp of entire fruits were monitored over the season by means of high-field NMR spectroscopy and T(2) relaxation time measurements, respectively, and compared with the corresponding ones of Hayward kiwifruits previously investigated. A more complete assignment of the (1)H spectrum with respect to that obtained previously was reported: histidine, phenylalanine, quercetin 3-rhamnoside, and epicatechin were identified. Metabolic profiling confirmed Zespri's earlier maturation compared with the two other varieties. The water state of entire kiwifruits was measured nondestructively on fruits attached to the plants or detached from the plants. T(2) relaxation times were found to be sensitive to the kiwifruit developmental stage.

Peach fruit: metabolic comparative analysis of two varieties with different resistances to insect attacks by NMR spectroscopy

The metabolite profile of aqueous extracts of two peach varieties, Percoca Romagnola 7 and Flaminia, with different susceptibilities to Ceratitis capitata attack was investigated by means of 1D and 2D high-field NMR spectroscopy. Water-soluble metabolites belonging to different classes such as organic acids (citric, fumaric, malic, quinic, shikimic, and succinic acids), sugars (fucose, fructose, fructose-6-phosphate, glucose, glucose-6-phosphate, rhamnose, sucrose, and xylose), amino acids (alanine, asparagine, isoleucine, threonine, and valine) and other metabolites such as myo-inositol, choline, trigonelline, catechin, chlorogenic and neochlorogenic acids, orthophosphate, and α-l-glycerophosphorylcholine were identified. The metabolite profile together with a suitable statistical analysis was used to make a comparison between the two varieties. The levels of glucose, xylose, myo-inositol, choline, isoleucine, and valine were found to be higher in Flaminia than in Percoca Romagnola 7 samples, whereas the levels of fumaric acid, alanine, quinic acid, sucrose, fucose, and chlorogenic and neochlorogenic acid were found to be higher in Percoca Romagnola 7 than in Flaminia samples.