| Résumé | This study shows the development and use of multi-dimensional chromatography-MS methods to generate comprehensive metabolite profiles and determine novel indicators of stress in juvenile Atlantic salmon. Aquaculture is one of the fastest growing sectors of the global agriculture-agrifood industry. In Canada, the aquaculture and related industries were valued at $800M in 2001. Stressors such as handling, change in water quality, and increased stocking density are unavoidable in aquaculture operations. Exposure to stressors is known to cause a generalized stress response in fish. This includes neuroendocrine (increase in cortisol and catecholamines), metabolic (increase in glucose) and cellular (production of heat shock proteins) responses. Depending on the duration of the stressor, fish can acclimate and adapt to reduce their stress response. We are developing metabolomics screening tools to evaluate stress in fish. In this metabolomics study, LC-MS based approaches were employed to identify changes in plasma metabolite profile of juvenile Atlantic salmon (Salmo salar) in response to short-term handling stress. Plasma samples were obtained from non-stressed fish (control) and fish subjected to handling stress (stressed). Following protein precipitation and molecular weight filtration (cut-off 3000 Da), polar and non-polar metabolites were extracted from the plasma using EnviTM-Carb or AccuBOND C18 solid-phase extraction cartridges, respectively. Separation of the polar metabolites was performed by hydrophilic interaction liquid chromatography (HILIC) using a TSK-GEL Amide-80 column (250×4.6mm ID), while an ACE3-C18 column (150×4.6mm ID) was employed for the separation of the non-polar metabolites. Detection of the metabolites was achieved with a 4000 QTRAP mass spectrometer (AB/Sciex) using both electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) in positive and negative-ion modes. Data from these studies revealed that the plasma samples contained significantly more metabolites which were highly polar in nature and these were observed during HILIC-MS analysis using electrospray ionization in the positive ion mode. Analysis of the metabolomics data using principal components analysis (PCA) with MATLAB clearly discerns the stressed from the non-stressed fish. As expected, levels of typical markers of stress such as cortisol were observed to increase in plasma from stressed fish. However, novel metabolites detected in non-stressed fish were observed to decrease in stressed fish. It is noteworthy that the PCA analysis also revealed an unexpected correlation between stress and the sex of the fish, suggesting that it might be important to consider the sex of the fish when studying the metabolomic response of fish to stressors. |
|---|
