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Abstract
Microbiome-directed dietary interventions such as microbiota-directed fibers (MDFs) have a proven track record in eliciting responses in beneficial gut microbes and are increasingly being promoted as an effective strategy to improve animal production systems. Here we used initial metataxonomic data on fish gut microbiomes as well as a wealth of a priori mammalian microbiome knowledge on α-mannooligosaccharides (MOS) and β-mannan-derived MDFs to study effects of such feed supplements in Atlantic salmon (Salmo salar) and their impact on its gut microbiome composition and functionalities. Our multi-omic analysis revealed that the investigated MDFs (two α-mannans and an acetylated β-galactoglucomannan), at a dose of 0.2% in the diet, had negligible effects on both host gene expression, and gut microbiome structure and function under the studied conditions. While a subsequent trial using a higher (4%) dietary inclusion of β-mannan significantly shifted the gut microbiome composition, there were still no biologically relevant effects on salmon metabolism and physiology. Only a single Burkholderia-Caballeronia-Paraburkholderia (BCP) population demonstrated consistent and significant abundance shifts across both feeding trials, although with no evidence of β-mannan utilization capabilities or changes in gene transcripts for producing metabolites beneficial to the host. In light of these findings, we revisited our omics data to predict and outline previously unreported and potentially beneficial endogenous lactic acid bacteria that should be targeted with future, conceivably more suitable, MDF strategies for salmon.
A multi-omic approach enables the reconstruction of microbial metabolic dynamics in the salmon gut in response to feed and feed supplements, outlining novel and potentially beneficial strategies to manipulate the salmon gut microbiota.
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1 Norwegian University of Life Sciences, Faculty of Chemistry, Biotechnology and Food Science, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X)
2 Norwegian University of Life Sciences, Faculty of Chemistry, Biotechnology and Food Science, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X); Norwegian University of Life Sciences, Faculty of Biosciences, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X)
3 The Globe Institute, University of Copenhagen, Center for Evolutionary Hologenomics, Copenhagen, Denmark (GRID:grid.5254.6) (ISNI:0000 0001 0674 042X)
4 Norwegian University of Life Sciences, Faculty of Chemistry, Biotechnology and Food Science, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X); Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment, Uppsala, Sweden (GRID:grid.6341.0) (ISNI:0000 0000 8578 2742)
5 Cargill Food Solutions – R&D – SST, Sandnes, Norway (GRID:grid.5254.6)
6 Cargill, Cargill Aqua Nutrition, Sandnes, Norway (GRID:grid.5254.6)
7 Norwegian University of Life Sciences, Faculty of Biosciences, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X)
8 SINTEF, Department of Biotechnology and Nanomedicine, Trondheim, Norway (GRID:grid.4319.f) (ISNI:0000 0004 0448 3150)
9 Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment, Uppsala, Sweden (GRID:grid.6341.0) (ISNI:0000 0000 8578 2742)
10 Norwegian University of Life Sciences, Faculty of Chemistry, Biotechnology and Food Science, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X); Norwegian University of Life Sciences, Faculty of Biosciences, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X); Translational Research Institute, Centre for Microbiome Research, School of Biomedical Sciences, Queensland University of Technology (QUT), Woolloongabba, Australia (GRID:grid.489335.0) (ISNI:0000000406180938)