Differential metabolic profiles associated to movement behaviour of stream-resident brown trout (Salmo trutta)

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2017
Author
Oromí Farrús, Neus
Jové Font, Mariona
Pascual Pons, Mariona
Royo Sánchez-Palencia, José Luis
Rocaspana, Rafel
Aparicio, Enric
Pamplona Gras, Reinald
Palau, Antoni
Sanuy i Castells, Delfí
Fibla Palazón, Joan
Portero Otín, Manuel
Suggested citation
Oromí Farrús, Neus; Jové Font, Mariona; Pascual Pons, Mariona; Royo Sánchez-Palencia, José Luis; Rocaspana, Rafel; Aparicio, Enric; ... Portero Otín, Manuel. (2017) . Differential metabolic profiles associated to movement behaviour of stream-resident brown trout (Salmo trutta). Plos One, 2017, vol. 12, núm. 7, p. 1-13. https://doi.org/10.1371/journal.pone.0181697.
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Abstract
The mechanisms that can contribute in the fish movement strategies and the associated behaviour can be complex and related to the physiology, genetic and ecology of each species. In the case of the brown trout (Salmo trutta), in recent research works, individual differences in mobility have been observed
in a population living in a high mountain river reach (Pyrenees, NE Spain). The population is mostly sedentary but a small percentage of individuals exhibit a mobile behavior, mainly upstream movements. Metabolomics can reflect changes in the physiological process and can determine different profiles depending on behaviour. Here, a non-targeted metabolomics approach was used to find possible changes in the blood metabolomic profile of S. trutta related to its movement behaviour, using a minimally invasive sampling. Results showed a differentiation in the metabolomic profiles of the trouts and different level concentrations of some metabolites (e.g. cortisol) according to the home range classification (pattern of movements: sedentary or mobile). The change in metabolomic profiles can generally occur during the upstream movement and probably reflects the changes in metabolite profile from the non-mobile season to mobile season. This study reveals the contribution of the metabolomic analyses to better understand the behaviour of organisms.
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http://hdl.handle.net/10459.1/60330
DOI
https://doi.org/10.1371/journal.pone.0181697
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Plos One, 2017, vol. 12, núm. 7, p. 1-13
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Except where otherwise noted, this item's license is described as cc- by (c) Oromi et al., 2017