Proton-NMR Metabolomics of Rainbow Trout Fed a Plant-Based Diet Supplemented with Graded Levels of a Protein-Rich Yeast Fraction Reveal Several Metabolic Processes Involved in Growth.


Journal

The Journal of nutrition
ISSN: 1541-6100
Titre abrégé: J Nutr
Pays: United States
ID NLM: 0404243

Informations de publication

Date de publication:
01 09 2020
Historique:
received: 30 04 2020
revised: 21 05 2020
accepted: 25 06 2020
pubmed: 18 8 2020
medline: 17 12 2020
entrez: 18 8 2020
Statut: ppublish

Résumé

Plant raw materials are commonly used in aquafeeds, as marine resources are unsustainable. However, full plant-based diets lead to poorer fish growth performance. We aimed to understand the metabolic effects of a yeast fraction as a protein supplement in a plant-based diet and to integrate such effects with phenotypic traits as a new approach to assess the interest of this raw material. Juvenile (49 g) rainbow trout (Oncorhynchus mykiss) were fed graded levels of a yeast protein-rich fraction (5% YST05, 10% YST10, 15% YST15) in a plant-based diet (PB) for 84 d. Final body weight, feed conversion ratio, and hepatosomatic and viscerosomatic indexes were measured. Plasma, liver, and muscle 1H-NMR fingerprints were analyzed with principal component analyses, and their metabolite patterns were clustered according to the yeast level to identify concomitant metabolic effects. A regression modeling approach was used to predict tissue metabolite changes from plasma fingerprints. In tissues, the patterns of metabolite changes followed either linear trends with the gradual inclusion of a yeast fraction (2 patterns out of 6 in muscle, 1 in liver) or quadratic trends (4 patterns in muscle, 5 in liver). Muscle aspartate and glucose (395 and 138% maximum increase in relative content compared with PB, respectively) revealing modification in energy metabolism, as well as modification of liver betaine (163% maximum increase) and muscle histidine (57% maximum decrease) related functions, indicates that the yeast fraction could improve growth in several ways. The highest correlation between measured and predicted metabolite intensities in a tissue based on plasma fingerprints was observed for betaine in liver (r = 0.80). These findings herald a new approach to assess the plurality of metabolic effects induced by diets and establish the optimal level of raw materials. They open the way for using plasma as a noninvasive matrix in trout nutrition studies.

Sections du résumé

BACKGROUND
Plant raw materials are commonly used in aquafeeds, as marine resources are unsustainable. However, full plant-based diets lead to poorer fish growth performance.
OBJECTIVE
We aimed to understand the metabolic effects of a yeast fraction as a protein supplement in a plant-based diet and to integrate such effects with phenotypic traits as a new approach to assess the interest of this raw material.
METHODS
Juvenile (49 g) rainbow trout (Oncorhynchus mykiss) were fed graded levels of a yeast protein-rich fraction (5% YST05, 10% YST10, 15% YST15) in a plant-based diet (PB) for 84 d. Final body weight, feed conversion ratio, and hepatosomatic and viscerosomatic indexes were measured. Plasma, liver, and muscle 1H-NMR fingerprints were analyzed with principal component analyses, and their metabolite patterns were clustered according to the yeast level to identify concomitant metabolic effects. A regression modeling approach was used to predict tissue metabolite changes from plasma fingerprints.
RESULTS
In tissues, the patterns of metabolite changes followed either linear trends with the gradual inclusion of a yeast fraction (2 patterns out of 6 in muscle, 1 in liver) or quadratic trends (4 patterns in muscle, 5 in liver). Muscle aspartate and glucose (395 and 138% maximum increase in relative content compared with PB, respectively) revealing modification in energy metabolism, as well as modification of liver betaine (163% maximum increase) and muscle histidine (57% maximum decrease) related functions, indicates that the yeast fraction could improve growth in several ways. The highest correlation between measured and predicted metabolite intensities in a tissue based on plasma fingerprints was observed for betaine in liver (r = 0.80).
CONCLUSIONS
These findings herald a new approach to assess the plurality of metabolic effects induced by diets and establish the optimal level of raw materials. They open the way for using plasma as a noninvasive matrix in trout nutrition studies.

Identifiants

pubmed: 32805000
pii: S0022-3166(22)02318-5
doi: 10.1093/jn/nxaa206
doi:

Substances chimiques

Dietary Proteins 0
Fungal Proteins 0

Types de publication

Journal Article Randomized Controlled Trial, Veterinary Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2268-2277

Informations de copyright

Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.

Auteurs

Simon Roques (S)

INRAE, Univ Pau & Pays Adour, E2S UPPA, UMR Nutrition, Métabolisme, Aquaculture, Saint Pée sur Nivelle, France.
Phileo by Lesaffre, Marcq-en-Baroeul, France.
PMB-Metabolome, INRAE, 2018, Bordeaux Metabolome Facility (doi: 10.15454/1.5572412770331912E12), MetaboHUB, Centre INRAE de Nouvelle Aquitaine Bordeaux, Villenave d'Ornon, France.

Catherine Deborde (C)

PMB-Metabolome, INRAE, 2018, Bordeaux Metabolome Facility (doi: 10.15454/1.5572412770331912E12), MetaboHUB, Centre INRAE de Nouvelle Aquitaine Bordeaux, Villenave d'Ornon, France.
INRAE, Univ Bordeaux, UMR Fruit Biology and Pathology, Centre INRAE de Nouvelle Aquitaine Bordeaux, Villenave d'Ornon, France.

Nadège Richard (N)

Phileo by Lesaffre, Marcq-en-Baroeul, France.

Yann Marchand (Y)

Le Gouessant, Lamballe, France.

Laurence Larroquet (L)

INRAE, Univ Pau & Pays Adour, E2S UPPA, UMR Nutrition, Métabolisme, Aquaculture, Saint Pée sur Nivelle, France.

Sylvain Prigent (S)

INRAE, Univ Bordeaux, UMR Fruit Biology and Pathology, Centre INRAE de Nouvelle Aquitaine Bordeaux, Villenave d'Ornon, France.

Sandrine Skiba-Cassy (S)

INRAE, Univ Pau & Pays Adour, E2S UPPA, UMR Nutrition, Métabolisme, Aquaculture, Saint Pée sur Nivelle, France.

Annick Moing (A)

PMB-Metabolome, INRAE, 2018, Bordeaux Metabolome Facility (doi: 10.15454/1.5572412770331912E12), MetaboHUB, Centre INRAE de Nouvelle Aquitaine Bordeaux, Villenave d'Ornon, France.
INRAE, Univ Bordeaux, UMR Fruit Biology and Pathology, Centre INRAE de Nouvelle Aquitaine Bordeaux, Villenave d'Ornon, France.

Benoit Fauconneau (B)

INRAE, Univ Pau & Pays Adour, E2S UPPA, UMR Nutrition, Métabolisme, Aquaculture, Saint Pée sur Nivelle, France.

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