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Enregistrement W6891681774 · doi:10.48336/wwz3-vk47

Impact of plant-based oils and other feed ingredients on growth, tissue composition, gene expression, and health of Atlantic salmon (Salmo salar)

2022· article· en· W6891681774 sur OpenAlexaff

Notice bibliographique

RevueMemorial University Research Repository (Memorial University) · 2022
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueAquaculture Nutrition and Growth
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesnon disponible
Mots-clésPolyunsaturated fatty acidNutrigenomicsTranscriptomeImmune systemLipid metabolismGeneFish oilFatty acidGene expressionAquaculture

Résumé

récupéré en direct d'OpenAlex

The ω6 to ω3 (ω6:ω3) fatty acid (FA) ratio is known to affect many biological processes (e.g. inflammation, FA metabolism) and human diseases. However, its impacts on salmon physiology, immune response, and the underlying molecular mechanisms are less well understood. The current thesis applied a nutrigenomics and lipidomics approach to study the impacts of plant-based feeds with varying dietary ω6:ω3 ratios and ω3 long chain polyunsaturated fatty acid (LC-PUFA) levels on farmed salmon growth, tissue composition and lipid metabolism, gene expression, and antibacterial immune response. In Chapter 2 Atlantic salmon were fed with diets containing the same sources and equal levels of marine and plant proteins, and differed in plant oil mixes to generate a range of ω6:ω3 (i.e. 0.3-2.7). A targeted qPCR study was used to measure the mRNA expression of lipid metabolism and eicosanoid synthesis-related genes in the liver. This study revealed that while growth performance and organ indices were not affected by dietary ω6:ω3, liver and muscle FA composition was highly reflective of the diet and suggested elongation and desaturation of 18:3ω3 and 18:2ω6. Compound-specific stable isotope analysis further demonstrated that liver 20:5ω3 and 20:4ω6 synthesis was largely driven by dietary 18:3ω3 and 18:2ω6, respectively. Moreover, significant correlations between LC-PUFA synthesis-related transcripts and liver LC-PUFA further supported FA biosynthesis. In Chapter 3, I used the same fish from the previous feeding trial in order to investigate how the two extreme ω6:ω3 diets (i.e. high ω6 and high ω3) affected the hepatic transcriptome (using 44K microarrays), and to identify novel biomarker genes that respond to variation in ω6:ω3. The microarray study identified transcripts with important roles in lipid metabolism (helz2a), cell proliferation (htra1b), immune and inflammatory response (lect2a, itgb5, helz2a, p43), control of muscle and neuronal cell development (mef2d), and translation (eif2a, eif4b1, p43). Further, the PPARα activation-related transcript helz2a was down-regulated by high ω6 diet compared with high ω3 diet, and two of its paralogues showed significant correlations with ω6 and ω3 FA in two tissues (liver, muscle). These data indicated their potential as biomarkers of tissue response to dietary ω6:ω3 variation. The focus of Chapter 4 was to apply a two-factorial design to evaluate if diets with different combinations of ω6:ω3 (high ω6, balanced, high ω3) and EPA+DHA levels (0.3, 1.0, or 1.4%, as formulated) impact head kidney lipid composition, and the transcript expression of genes involved in FA and eicosanoid metabolism (using qPCR). Head kidney FA composition was reflective of the diet and responded to ω6:ω3 variation. Proportions of 20:5ω3 were similar among fish fed 0.3% EPA+DHA with high ω3, 1% EPA+DHA (both high ω3 and high ω6 treatments) and 1.4% EPA+DHA/balanced fed fish, although dietary 20:5ω3 varied by 2.5- to 3-fold. Further, positive correlations were identified between head kidney ω3 LC-PUFA and elovl5a transcript levels. This suggested that high dietary 18:3ω3 promoted the synthesis of ω3 LC-PUFA in salmon fed lower dietary EPA+DHA levels (0.3%). This Chapter also showed significant correlations between head kidney FA composition and the expression of eicosanoid synthesis-related transcripts (i.e. 5loxa, 5loxb, cox1, cox2, ptges2, ptges3, and pgds), which illustrated the constitutive relationships among FA and eicosanoid metabolism in salmon. In Chapter 5 salmon were fed high ω6 and high ω3 diets combined with two EPA+DHA levels (0.3 and 1.0% of diet) to investigate dietary impacts on antibacterial and eicosanoid responses. Eicosanoid-metabolism-related transcripts (e.g. cox1, 5loxa, 5loxb, pgds, lkha4) in the head kidney were down-regulated in formalin-killed Aeromonas salmonicida (ASAL)-injected compared with the phosphate-buffered saline (PBS)-injected fish (within diet), suggesting an attempt to mitigate the proinflammatory response in bacterin-challenged fish. Fish fed 0.3% EPA+DHA with high ω6 diet showed the strongest fold-change induction (ASAL vs. PBS) of antibacterial genes (ccl19b, il8, il10, il8, saa5, hamp). Further, this Chapter showed positive correlations between head kidney ω6 PUFA and the transcript expression of immune-related genes (e.g. il8, il10, hamp, camp, stlr5, lect2). These findings suggested that 0.3%EPA+DHA with high ω6 diet may have enhanced the innate antibacterial immune response of Atlantic salmon. Finally, diet and ASAL and/or PBS injection significantly impacted the plasma prostaglandin (PGE2, PGF3α) levels [measured with electrospray ionization mass spectrometry (ESI-MS/MS)] of salmon. The 0.3%EPA+DHA with high ω6 diet also resulted in lower levels of PGE2 in ASAL- when compared with PBS-injected fish, and this was concurrent with lower head kidney expression of PGE2 receptor-encoding transcript (i.e. ptger4a).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,329
Score d'incertitude au seuil0,950

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,032
Tête enseignante GPT0,264
Écart entre enseignants0,232 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2022
Routes d'admission1
Résumé présentoui

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