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Toffali K.,University of Verona | Ceoldo S.,University of Verona | Stocchero M.,S IN Soluzioni Informatiche | Levi M.,University of Verona | Guzzo F.,University of Verona
Plant Science | Year: 2013

Plants produce a vast array of secondary metabolites, many of which have important biological properties in animals when consumed as part of the diet. Interestingly, although the activities and benefits of plant secondary metabolites in animals are well established, comparatively little is known about the endogenous functions of these compounds in plants. One way to investigate the role of secondary products in plants is to modify the secondary metabolome and investigate the impact of such modifications on the phenotype.We have designed a novel feeding approach using different hydroxycinnamic acids (HCAs) and the cyanidin precursor dihydroquercetin (DHQ) to modify the metabolome of carrot R3M suspension cells. This strategy increased the accumulation of specific metabolites in a predictable way, and provided novel insights into the carrot phenylpropanoid pathway, suggesting that (a) cells use HCA hexose esters as substrates in the biosynthetic pathway leading to the accumulation of the various HCA derivatives and (b) p-coumaric acid derivative levels play a key roles in the regulation the flux of HCAs along the pathway.Moreover, this rapid strategy for metabolome modification does not depend on the availability of molecular tools or knowledge and can therefore be applied to any plant species. © 2013 Elsevier Ireland Ltd.

Carraro S.,University of Padua | Giordano G.,University of Padua | Pirillo P.,University of Padua | Maretti M.,University of Padua | And 5 more authors.
Journal of Pediatrics | Year: 2015

Objectives To assess a group of adolescents with bronchopulmonary dysplasia (BPD) from a biochemical-metabolic standpoint, applying the metabolomic approach to studying their exhaled breath condensate (EBC). Study design Twenty adolescents with BPD (mean age 14.8 years) and 15 healthy controls (mean age 15.2 years) were recruited for EBC collection, exhaled nitric oxide measurement, and spirometry. The EBC samples were analyzed using a metabolomic approach based on mass spectrometry. The obtained spectra were analyzed using multivariate statistical analysis tools. Results A reliable Orthogonal Projections to Latent Structures-Discriminant Analysis model showed a clear discrimination between cases of BPD and healthy controls (R2 = 0.95 and Q2 = 0.92). The search for putative biomarkers identified an altered complex lipid profile in the adolescents with BPD. Conclusions The metabolomic analysis of EBC distinguishes cases of BPD from healthy individuals, suggesting that the lung of survivors of BPD is characterized by long-term metabolic abnormalities. The search for putative biomarkers indicated a possible role of an altered surfactant composition, which may persist far beyond infancy. © 2015 Elsevier Inc.

Consonni R.,CNR Institute for Macromolecular Studies | Cagliani L.R.,CNR Institute for Macromolecular Studies | Stocchero M.,S IN Soluzioni Informatiche | Porretta S.,Stazione Sperimentale per LIndustria Delle Conserve Alimentari
Journal of Agricultural and Food Chemistry | Year: 2010

Nuclear magnetic resonance (NMR) is nowadays largely used as valid tool in metabolomic applications. In this study, the metabolite content of Italian and Chinese tomato paste at different concentration rates of two production years (2007 and 2008) was investigated with the aim of building a robust geographical differentiation statistical model. A total of 119 tomato paste samples were analyzed by 1H NMR and multivariate data analysis tools, in particular using bidirectional orthogonal projection to latent structures-discriminant analysis (02PLS - DA). This technique is well-suited for noisy and correlated variables and was recently adopted to obtain robust classification models, having a clear interpretation of the systematic variation useful to characterize each class. In the present study, the analysis of latent space underlying the classification model allowed us to understand the role played by the production year on geographical discrimination. The 02PLS-DA model performed considering only tomato paste samples of 2007 was capable of predicting the geographical origin of all analyzed samples. The effect of the production year therefore resulted in not affecting the geographical origin discrimination. © 2010 American Chemical Society.

Mattarucchi E.,European Commission - Joint Research Center Ispra | Stocchero M.,S IN Soluzioni Informatiche | Moreno-Rojas J.M.,European Commission - Joint Research Center Ispra | Giordano G.,European Commission - Joint Research Center Ispra | And 3 more authors.
Journal of Agricultural and Food Chemistry | Year: 2010

The aim of this study was to asses the applicability of LC-MS profiling to authenticate a selected Trappist beer as part of a program on traceability funded by the European Commission. A total of 232 beers were fingerprinted and classified through multivariate data analysis. The selected beer was clearly distinguished from beers of different brands, while only 3 samples (3.5% of the test set) were wrongly classified when compared with other types of beer of the same Trappist brewery. The fingerprints were further analyzed to extract the most discriminating variables, which proved to be sufficient for classification, even using a simplified unsupervised model. This reduced fingerprint allowed us to study the influence of batch-to-batch variability on the classification model. Our results can easily be applied to different matrices and they confirmed the effectiveness of LC-MS profiling in combination with multivariate data analysis for the characterization of food products. © 2010 American Chemical Society.

Carraro S.,University of Padua | Giordano G.,University of Padua | Reniero F.,European Commission - Joint Research Center Ispra | Carpi D.,European Commission - Joint Research Center Ispra | And 3 more authors.
Allergy: European Journal of Allergy and Clinical Immunology | Year: 2013

Background Asthma is a heterogeneous disease and its different phenotypes need to be better characterized from a biochemical-inflammatory standpoint. This study aimed to apply the metabolomic approach to exhaled breath condensate (breathomics) to discriminate different asthma phenotypes, with a particular focus on severe asthma in children. Methods In this cross-sectional study, we recruited 42 asthmatic children (age, 8-17 years): 31 with nonsevere asthma (treated with inhaled steroids or not) and 11 with severe asthma. Fifteen healthy children were enrolled as controls. Children performed exhaled nitric oxide measurement, spirometry, exhaled breath condensate (EBC) collection. Condensate samples were analyzed using a metabolomic approach based on mass spectrometry. Results A robust Bidirectional-Orthogonal Projections to Latent Structures-Discriminant Analysis (O2PLS-DA) model was found for discriminating both between severe asthma cases and healthy controls (R2 = 0.93; Q2 = 0.75) and between severe asthma and nonsevere asthma (R 2 = 0.84; Q2 = 0.47). The metabolomic data analysis leads to a robust model also when the 3 groups of children were considered altogether (K = 0.80), indicating that each group is characterized by a specific metabolomic profile. Compounds related to retinoic acid, adenosine and vitamin D (Human Metabolome Database) were relevant for the discrimination between groups. Conclusion The metabolomic profiling of EBC could clearly distinguish different biochemical-metabolic profiles in asthmatic children and enabled the severe asthma phenotype to be fully discriminated. The breathomics approach may therefore be suitable for discriminating between different asthma metabolic phenotypes. © 2012 John Wiley & Sons A/S.

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