Detalle de: Untargeted metabolomics approach for unraveling robust biomarkers of nutritional status in fasted gilthead sea bream ( Sparus aurata )
| Title | Untargeted metabolomics approach for unraveling robust biomarkers of nutritional status in fasted gilthead sea bream ( Sparus aurata ) |
| Abstract |
A metabolomic study has been performed to identify sensitive and robust biomarkers of malnutrition in farmed fish, using gilthead sea bream ( Sparus aurata ) as a model. The metabolomic fingerprinting of serum from fasted fish was assessed by means of ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. More than 15,000 different m/z ions were detected and Partial Least Squares–Discriminant analysis allowed a clear differentiation between the two experimental groups (fed and 10-day fasted fish) with more than 90% of total variance explained by the two first components. The most significant metabolites (up to 45) were elucidated on the basis of their tandem mass spectra with a broad representation of amino acids, oligopeptides, urea cycle metabolites, L-carnitine-related metabolites, glutathione-related metabolites, fatty acids, lysophosphatidic acids, phosphatidylcholines as well as biotin- and noradrenaline-related metabolites. This untargeted approach highlighted important adaptive responses in energy and oxidative metabolism, contributing to identify robust and nutritionally-regulated biomarkers of health and metabolic condition that will serve to assess the welfare status of farmed fish. |
| Apa Reference | Gil-Solsona, R., Nácher-Mestre, J., Lacalle-Bergeron, L., Sancho, J.V., Calduch-Giner, J.A., Hernández, F. & Pérez-Sánchez, J. (2017). Untargeted metabolomics approach for unraveling robust biomarkers of nutritional status in fasted gilthead sea bream ( Sparus aurata ). PeerJ, 5, e2920. 10.7717/peerj.2920 |
| Doi | 10.7717/peerj.2920 |
| Publication Date | 26 Jan 2017 |
| Publication Type | Article |
| Researcher | Jaume Pérez Sánchez |
| Ontology | Metabolomics, Metabolome profiling, Multivariate statistics, Metabolite Biomarker Identification, Marine Systems |
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