Metabolic profiling of Daphnia magna exposed to environmental stressors by GC-MS and chemometric tools
Introduction: Climate change is a major concern for the scientific community, demanding novel information about the effects of environmental stressors on living organisms. Metabolic profiling is required for achieving the most extensive possible range of compounds and their concentration changes on stressed conditions. Objectives: Individuals of the crustacean species Daphnia magna were exposed to three different abiotic factors linked to global climate change: high salinity, high temperature levels and hypoxia. Advanced chemometric tools were used to characterize the metabolites affected by the exposure. Method: An exploratory analysis of gas chromatography-mass spectrometry (GC–MS) data was performed to discriminate between control and exposed daphnid samples. Due to the complexity of these GC–MS data sets, a comprehensive untargeted analysis of the full scan data was performed using multivariate curve resolution-alternating least squares (MCR-ALS) method. This approach enabled to resolve most of the metabolite signals from interference peaks caused by derivatization reactions. Metabolites with significant changes in their peak areas were tentatively identified and the involved metabolic pathways explored. Results: D. magna metabolic biomarkers are proposed for the considered physical factors. Metabolites related with energy metabolic pathways including some amino acids, carbohydrates, organic acids and nucleosides were identified as potential biomarkers of the investigated treatments. Conclusions: The proposed untargeted GC–MS metabolomics strategy and multivariate data analysis tools were useful to investigate D. magna metabolome under environmental stressed conditions. © 2016, Springer Science+Business Media New York.
| Main Authors: | , , , , |
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| Format: | artículo biblioteca |
| Language: | English |
| Published: |
Springer
2016-05-01
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| Subjects: | Chemometric tools, Daphnia magna, Environmental stressors, Gas chromatography-mass spectrometry, Metabolic profiling, |
| Online Access: | http://hdl.handle.net/10261/133643 |
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