Modulation of Fecal Metabolites by Heat Stress and Diet, and Their Association with Inflammation and Leaky Gut Markers in Dairy Cows
Notice bibliographique
Résumé
The analysis of fecal metabolite profiles could provide novel insights into the mechanisms underlying animal responses to environmental stressors and diet. We aimed to evaluate the effects of a 14-day heat stress period and of dietary mineral and vitamin supplementation under heat stress on fecal metabolite profiles and to investigate their associations with physiological markers of heat stress, leaky gut, and inflammation in lactating dairy cows. Twelve multiparous Holstein cows (42.2 ± 5.6 kg milk/d; 83.4 ± 27.1 DIM) were enrolled in an experiment in a split-plot design. The main plot was the level of dietary vitamin E and Se, as follows: (1) low (L-ESe; 20 IU/kg vitamin E, 0.3 ppm Se) or (2) high (H-ESe 200 IU/kg vitamin E, 1.2 ppm Se). Within each plot, six cows were randomly assigned to either (1) heat stress (HS; Total Humidity Index (THI): 82), (2) pair-feeding in thermoneutrality (TNPF; THI = 64), or (3) HS with vitamin D3 and Ca supplementation (HS+DCa; 1820 IU/kg and 1.5% Ca; THI: 82) in a replicated 3 × 3 Latin square design with 14-day periods and 7-day washouts. The concentrations of 94 metabolites were determined in fecal samples, including amino acids, fatty acids, biogenic amines, and vitamins. Relative to the L-ESe group, the H-ESe group increased α-tocopherol by threefold, whereas δ-tocopherol was decreased by 78% (PFDR < 0.01). Nevertheless, correlation analysis between α-tocopherol and all the others fecal metabolites or physiological heat stress measures did not show significant associations. No interactions between main plot and treatments were observed. Relative to TNPF, HS increased plasma tumor necrosis factor-alpha (TNF-α), plasma lipopolysaccharide-binding protein (LBP), milk somatic cell counts (SCC), respiratory rates, rectal temperatures, fecal tridecylic and myristic acids, vitamin B7, and retinol, whereas it decreased fecal amino acids such as histidine, methyl histidine, acetyl ornithine, and arginine (PFDR < 0.05). In contrast, HS+DCa increased fecal methyl histidine concentrations and reduced milk SCC, plasma TNF-α, and LBP, as well as rectal temperatures. Discriminant analysis revealed fecal histidine, taurine, acetyl ornithine, arginine, β-alanine, ornithine, butyric + iso-butyric acid, plasma non-esterified fatty acids, TNF-α, LBP, C-reactive protein, and milk SCC were predictive of HS. Several metabolites were predictive of HS+DCa, although only tryptophan was discriminant relative to HS. In conclusion, both heat stress and the supplementation of vitamin D3 and Ca can influence the fecal metabolome of dairy cows experiencing heat stress, independently of dietary levels of vitamin E and Se. Our results suggest that some fecal metabolites are well associated with physiological measures of heat stress and may thus provide insights into the gut-level changes taking place under heat stress in dairy cows.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».