31
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Molecular pathways associated with the nutritional programming of plant-based diet acceptance in rainbow trout following an early feeding exposure

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The achievement of sustainable feeding practices in aquaculture by reducing the reliance on wild-captured fish, via replacement of fish-based feed with plant-based feed, is impeded by the poor growth response seen in fish fed high levels of plant ingredients. Our recent strategy to nutritionally program rainbow trout by early short-term exposure to a plant-based (V) diet versus a control fish-based (M) diet at the first-feeding fry stage when the trout fry start to consume exogenous feed, resulted in remarkable improvements in feed intake, growth and feed utilization when the same fish were challenged with the diet V (V-challenge) at the juvenile stage, several months following initial exposure. We employed microarray expression analysis at the first-feeding and juvenile stages to deduce the mechanisms associated with the nutritional programming of plant-based feed acceptance in trout.

          Results

          Transcriptomic analysis was performed on rainbow trout whole fry after 3 weeks exposure to either diet V or diet M at the first feeding stage (3-week), and in the whole brain and liver of juvenile trout after a 25 day V-challenge, using a rainbow trout custom oligonucleotide microarray. Overall, 1787 (3-week + Brain) and 924 (3-week + Liver) mRNA probes were affected by the early-feeding exposure. Gene ontology and pathway analysis of the corresponding genes revealed that nutritional programming affects pathways of sensory perception, synaptic transmission, cognitive processes and neuroendocrine peptides in the brain; whereas in the liver, pathways mediating intermediary metabolism, xenobiotic metabolism, proteolysis, and cytoskeletal regulation of cell cycle are affected. These results suggest that the nutritionally programmed enhanced acceptance of a plant-based feed in rainbow trout is driven by probable acquisition of flavour and feed preferences, and reduced sensitivity to changes in hepatic metabolic and stress pathways.

          Conclusions

          This study outlines the molecular mechanisms in trout brain and liver that accompany the nutritional programming of plant-based diet acceptance in trout, reinforces the notion of the first-feeding stage in oviparous fish as a critical window for nutritional programming, and provides support for utilizing this strategy to achieve improvements in sustainability of feeding practices in aquaculture.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-016-2804-1) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references117

          • Record: found
          • Abstract: found
          • Article: not found

          Cluster analysis and display of genome-wide expression patterns.

          A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Integration of biological networks and gene expression data using Cytoscape.

            Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Expanding the utilization of sustainable plant products in aquafeeds: a review

                Bookmark

                Author and article information

                Contributors
                bmukundh@gmail.com
                panserat@st-pee.inra.fr
                Mathilde.Dupont-Nivet@jouy.inra.fr
                edwige.quillet@jouy.inra.fr
                jerome.montfort@rennes.inra.fr
                alecam@rennes.inra.fr
                medale@st-pee.inra.fr
                kaushik@st-pee.inra.fr
                inge.geurden@st-pee.inra.fr
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                13 June 2016
                13 June 2016
                2016
                : 17
                : 449
                Affiliations
                [ ]INRA, UR1067 NUMEA Nutrition, Métabolisme et Aquaculture, Pôle d’Hydrobiologie INRA, 64310 Saint Pée-sur-Nivelle, France
                [ ]INRA, UMR1313 GABI Génétique Animale et Biologie Intégrative, 78350 Jouy-en-Josas, France
                [ ]INRA, UR 1037 Laboratoire de Physiologie et Génomique des Poissons (LPGP), Rennes, France
                Article
                2804
                10.1186/s12864-016-2804-1
                4907080
                27296167
                b2cbea7e-03b6-4f86-941b-95a50f57a3a1
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 11 November 2015
                : 27 May 2016
                Funding
                Funded by: INRA, Departement PHASE
                Award ID: Crédit Incitatif
                Funded by: FUI (regional and national French public funding)
                Award ID: Vegeaqua
                Funded by: EU Seventh Framework Programme
                Award ID: ARRAINA project No. 288925: Advanced Research Initiatives for Nutrition & Aquaculture
                Funded by: INRA MRI postdoctoral research fellowship
                Award ID: INRA-WUR Aquaculture Platform
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Genetics
                Genetics

                Comments

                Comment on this article