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Detalle de: Combined effects of salinity, temperature and hypoxia on Daphnia magna metabolism

Title Combined effects of salinity, temperature and hypoxia on Daphnia magna metabolism
Abstract

Metabolic changes of Daphnia magna pools due different abiotic factors linked to global climate change (salinity, temperature and hypoxia) were investigated using untargeted GC-MS and advanced chemometric strategies using a three factors two-level full factorial experimental design (DoE). Effects of these three factors and identity of the metabolites whose concentrations changed because of them were investigated. The simultaneous analysis of GC-MS data sets using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) allowed the resolution of the elution and mass spectra profiles of a large number of D. magna metabolites. Changes in peak areas of these metabolites were then analyzed by Principal Component Analysis (PCA), by ANOVA-Simultaneous Component Analysis (ASCA) and by Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), and the combined effects of the three investigated stressors were assessed. Results confirmed the strong influence of increasing environmental salinity levels on the D. magna metabolome. This impact was specially highlighted by changes on the cellular content of carbohydrates, fatty acids, organic acids and amino acid molecules. In contrast, these effects were less significant for the other two factors (temperature and hypoxia) at the moderate stressing experimental conditions investigated in this work when they were not combined with salinity.

Apa Reference Garreta-Lara, E., Campos, B., Barata, C., Lacorte, S. & Tauler, R. (2018). Combined effects of salinity, temperature and hypoxia on Daphnia magna metabolism. Science of The Total Environment, 610-611, 602-612. 10.1016/j.scitotenv.2017.05.190
Doi 10.1016/j.scitotenv.2017.05.190
Publication Date Jan 2018
Publication Type Article
Researcher Romá Tauler
Ontology Experimental design, Metabolomics, Metabolome profiling, Multivariate statistics, Climate change adaptation, Dimensionality reduction
Research Groups
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