Introducció de material exòtic per a l'obtenció de blat de moro farratger: resultats preliminars

Peer Reviewe

Semi-Targeted Profiling of the Lipidome Changes Induced by Erysiphe Necator in Disease-Resistant and Vitis vinifera L. Varieties

The ascomycete Erysiphe necator is a serious pathogen in viticulture. Despite the fact that some grapevine genotypes exhibit mono-locus or pyramided resistance to this fungus, the lipidomics basis of these genotypes’ defense mechanisms remains unknown. Lipid molecules have critical functions in plant defenses, acting as structural barriers in the cell wall that limit pathogen access or as signaling molecules after stress responses that may regulate innate plant immunity. To unravel and better understand their involvement in plant defense, we used a novel approach of ultra-high performance liquid chromatography (UHPLC)-MS/MS to study how E. necator infection changes the lipid profile of genotypes with different sources of resistance, including BC4 (Run1), “Kishmish vatkhana” (Ren1), F26P92 (Ren3; Ren9), and “Teroldego” (a susceptible genotype), at 0, 24, and 48 hpi. The lipidome alterations were most visible at 24 hpi for BC4 and F26P92, and at 48 hpi for “Kishmish vatkhana”. Among the most abundant lipids in grapevine leaves were the extra-plastidial lipids: glycerophosphocholine (PCs), glycerophosphoethanolamine (PEs) and the signaling lipids: glycerophosphates (Pas) and glycerophosphoinositols (PIs), followed by the plastid lipids: glycerophosphoglycerols (PGs), monogalactosyldiacylglycerols (MGDGs), and digalactosyldiacylglycerols (DGDGs) and, in lower amounts lyso-glycerophosphocholines (LPCs), lyso-glycerophosphoglycerols (LPGs), lyso-glycerophosphoinositols (LPIs), and lyso-glycerophosphoethanolamine (LPEs). Furthermore, the three resistant genotypes had the most prevalent down-accumulated lipid classes, while the susceptible genotype had the most prevalent up-accumulated lipid classes

Food intake biomarkers for berries and grapes

Grapes and berries are two types of widely consumed fruits characterized by a high content in different phytochemicals. However, their accurate dietary assessment is particularly arduous, because of the already wide recognized bias associated with self-reporting methods, combined with the large range of species and cultivars and the fact that these fruits are popularly consumed not only in fresh and frozen forms but also as processed and derived products, including dried and canned fruits, beverages, jams, and jellies. Reporting precise type and/or quantity of grape and berries in FFQ or diaries can obviously be affected by errors. Recently, biomarkers of food intake (BFIs) rose as a promising tool to provide accurate information indicating consumption of certain food items. Protocols for performing systematic reviews in this field, as well as for assessing the validity of candidate BFIs have been developed within the Food Biomarker Alliance (FoodBAll) Project. This paper aims to evaluate the putative BIFs for blueberries, strawberries, raspberries, blackberries, cranberries, blackcurrant, and grapes. Candidate BFIs for grapes were resveratrol metabolites and tartaric acid. The metabolites considered as putative BFI for berries consumption were mostly anthocyanins derivatives together with several metabolites of ellagitannins and some aroma compounds. However, identification of BFIs for single berry types encountered more difficulties. In the absence of highly specific metabolites reported to date, we suggested some multi-metabolite panels that may be further investigated as putative biomarkers for some berry fruits

Food intake biomarkers for apple, pear, and stone fruit

Fruit is a key component of a healthy diet. However, it is still not clear whether some classes of fruit may be more beneficial than others and whether all individuals whatever their age, gender, health status, genotype, or gut microbiota composition respond in the same way to fruit consumption. Such questions require further observational and intervention studies in which the intake of a specific fruit can be precisely assessed at the population and individual levels. Within the Food Biomarker Alliance Project (FoodBAll Project) under the Joint Programming Initiative 'A Healthy Diet for a Healthy Life', an ambitious action was undertaken aiming at reviewing existent literature in a systematic way to identify validated and promising biomarkers of intake for all major food groups, including fruits. This paper belongs to a series of reviews following the same BFIRev protocol and is focusing on biomarkers of pome and stone fruit intake. Selected candidate biomarkers extracted from the literature search went through a validation process specifically developed for food intake biomarkers

Discovery of intake biomarkers of lentils, chickpeas and white beans by untargeted LC-MS metabolomics in serum and urine.

Scope: To identify reliable biomarkers of food intake (BFIs) of pulses. Methods and results: A randomized crossover postprandial intervention study is conducted on 11 volunteers who consumed lentils, chickpeas, and white beans. Urine and serum samples are collected at distinct postprandial time points up to 48 h, and analyzed by LC-HR-MS untargeted metabolomics. Hypaphorine, trigonelline, several small peptides, and polyphenol-derived metabolites prove to be the most discriminating urinary metabolites. Two arginine-related compounds, dopamine sulfate and epicatechin metabolites, with their microbial derivatives, are identified only after intake of lentils, whereas protocatechuic acid is identified only after consumption of chickpeas. Urinary hydroxyjasmonic and hydroxydihydrojasmonic acids, as well as serum pipecolic acid and methylcysteine, are found after white bean consumption. Most of the metabolites identified in the postprandial study are replicated as discriminants in 24 h urine samples, demonstrating that in this case the use of a single, noninvasive sample is suitable for revealing the consumption of pulses. Conclusions: The results of the present untargeted metabolomics work reveals a broad list of metabolites that are candidates for use as biomarkers of pulse intake. Further studies are needed to validate these BFIs and to find the best combinations of them to boost their specificity

Effects of a long-term lifestyle intervention on metabolically healthy women with obesity: Metabolite profiles according to weight loss response

BACKGROUND & AIMS: The benefits of weight loss in subjects with metabolically healthy obesity (MHO) are still a matter of controversy. We aimed to identify metabolic fingerprints and their associated pathways that discriminate women with MHO with high or low weight loss response after a lifestyle intervention, based on a hypocaloric Mediterranean diet (MedDiet) and physical activity. METHODS: A UPLC-Q-Exactive-MS/MS metabolomics workflow was applied to plasma samples from 27 women with MHO before and after 12 months of a hypocaloric weight loss intervention with a MedDiet and increased physical activity. The subjects were stratified into two age-matched groups according to weight loss: 10% (high weight loss group, HWL). Random forest analysis was performed to identify metabolites discriminating between the LWL and the HWL as well as within-status effects. Modulated pathways and associations between metabolites and anthropometric and biochemical variables were also investigated. RESULTS: Thirteen metabolites discriminated between the LWL and the HWL, including 1,5-anhydroglucitol, carotenediol, 3-(4-hydroxyphenyl)lactic acid, N-acetylaspartate and several lipid species (steroids, a plasmalogen, sphingomyelins, a bile acid and long-chain acylcarnitines). 1,5-anhydroglucitol, 3-(4-hydroxyphenyl)lactic acid and sphingomyelins were positively associated with weight variables whereas N-acetylaspartate and the plasmalogen correlated negatively with them. Changes in very long-chain acylcarnitines and hydroxyphenyllactic levels were observed in the HWL and positively correlated with fasting glucose, and changes in levels of the plasmalogen negatively correlated with insulin resistance. Additionally, the cholesterol profile was positively associated with changes in acid hydroxyphenyllactic, sphingolipids and 1,5-AG. CONCLUSIONS: Higher weight loss after a hypocaloric MedDiet and increased physical activity for 12 months is associated with changes in the plasma metabolome in women with MHO. These findings are associated with changes in biochemical variables and may suggest an improvement of the cardiometabolic risk profile in those patients that lose greater weight. Further studies are needed to investigate whether the response of those subjects with MHO to this intervention differs from those with unhealthy obesity

Impact in Plasma Metabolome as Effect of Lifestyle Intervention for Weight-Loss Reveals Metabolic Benefits in Metabolically Healthy Obese Women

Little is known regarding metabolic benefits of weight loss (WL) on the metabolically healthy obese (MHO) patients. We aimed to examine the impact of a lifestyle weight loss (LWL) treatment on the plasma metabolomic profile in MHO individuals. Plasma samples from 57 MHO women allocated to an intensive LWL treatment group (TG, hypocaloric Mediterranean diet and regular physical activity, n = 30) or to a control group (CG, general recommendations of a healthy diet and physical activity, n = 27) were analyzed using an untargeted 1H NMR metabolomics approach at baseline, after 3 months (intervention), and 12 months (follow-up). The impact of the LWL intervention on plasma metabolome was statistically significant at 3 months but not at follow-up and included higher levels of formate and phosphocreatine and lower levels of LDL/VLDL (signals) and trimethylamine in the TG. These metabolites were also correlated with WL. Higher myo-inositol, methylguanidine, and 3-hydroxybutyrate, and lower proline, were also found in the TG; higher levels of hippurate and asparagine, and lower levels of 2-hydroxybutyrate and creatine, were associated with WL. The current findings suggest that an intensive LWL treatment, and the consequent WL, leads to an improved plasma metabolic profile in MHO women through its impact on energy, amino acid, lipoprotein, and microbial metabolism. Keywords: NMR; hypocaloric diet; metabolically healthy obesity; metabolomics; physical activity

Biomarkers of intake for coffee, tea and sweetened beverages

Non-alcoholic beverages are important sources of nutrients and bioactive compounds that may influence human health and increase or decrease the risk of chronic diseases. A wide variety of beverage constituents are absorbed in the gut, found in the systemic circulation and excreted in urine. They may be used as compliance markers in intervention studies or as biomarkers of intake to improve measurements of beverage consumption in cohort studies and reveal new associations with disease outcomes that may have been overlooked when using dietary questionnaires. Here, biomarkers of intake of some major non-alcoholic beverages coffee, tea, sugar-sweetened beverages, and low-calorie-sweetened beverages are reviewed. Results from dietary intervention studies and observational studies are reviewed and analyzed, and respective strengths and weaknesses of the various identified biomarkers discussed. A variety of compounds derived from phenolic acids, alkaloids, and terpenes were shown to be associated with coffee intake and trigonelline and cyclo(isoleucylprolyl) showed a particularly high specificity for coffee intake. Epigallocatechin and 4′-O-methylepigallocatechin appear to be the most sensitive and specific biomarkers for green or black tea, while 4-O-methylgallic acid may be used to assess black tea consumption. Intake of sugar-sweetened beverages has been assessed through the measurement of carbon-13 enrichment of whole blood or of blood alanine in North America where sugar from sugarcane or corn is used as a main ingredient. The most useful biomarkers for low-calorie-sweetened beverages are the low-calorie sweeteners themselves. Further studies are needed to validate these biomarkers in larger and independent populations and to further evaluate their specificity, reproducibility over time, and fields of application