Independent but Synergistic Effects of Dairy and Exercise Training on Gut Microbiota, Serum Metabolomics and Weight Gain Attenuation in Obese Rats
Notice bibliographique
Résumé
Background As research has shown that positive energy balance is a predominant factor underlying the development of obesity, it is important to seek strategies that can be used to augment the effects of exercise in the prevention and treatment of the condition. Recent studies have shown that dairy may have a protective effect against the development of obesity in both humans and rats. However, few studies have examined the individual and combined effects of dairy intake and endurance exercise. Purpose The purpose of this study was to compare individual and combined effects of dairy and endurance exercise training on gut microbiota abundance and serum metabolites in relation to metabolic parameters including weight gain, adiposity, and circulating mediators (e.g. glucose, insulin, free fatty acids). Methods An 8‐week feeding intervention of a high‐fat, high‐sugar diet was used to induce obesity in male Sprague‐Dawley rats. Rats were assigned to one of four groups for 6 wk: i) high fat (n=12), ii) dairy (n=14), iii) dairy+exercise (n=9), and iv) exercise alone (n=9). Rats underwent acclimation sessions prior to commencing training. Incremental exercise training took place 5 d/wk on a motorized treadmill. Fresh fecal samples were collected prior to sacrifice. Total DNA was extracted and quantified, and microbial profiling was conducted using qPCR. Data are reported as relative abundance. Serum metabolmics from fasting samples were assessed by 1 H‐NMR, ICP‐MS and GC‐MS. Results Dairy+exercise treatment attenuated weight gain more than either dairy or exercise alone (p<0.05). Microbial profiling of fecal matter revealed that dairy but not exercise increased the relative abundance of Bifidobacterium spp.(p<0.05). Exercise alone increased the relative abundance of Methanobrevibacter spp., Akkermansia muciniphila, Collinsella Aerfaciens, and Bacteroides/Prevotella spp., while the combination of dairy+exercise negated these impacts (p<0.05). In addition, dairy, exercise, and the combination of dairy+exercise reduced the abundance of Clostridium Cluster XI, a bacterial group previously shown to be elevated with high fat feeding. Serum metabolomics profiling demonstrated the most robust separation with dairy treatments (p<0.05). Metabolites driving the separation included those most closely associated with one carbon metabolism, TCA cycle intermediates, and those associated with dairy consumption (e.g. calcium, potassium). Conclusion Dairy and exercise treatments appeared to have distinct impacts on both microbial and serum metabolomics profiles. Importantly, the impacts of dairy were profound and larger than anticipated, especially on microbial profiles. This work demonstrates that the impacts of dairy and exercise were distinct but additive on these parameters, likely working synergistically to maintain body weight. Support or Funding Information Dairy Farmers of Canada (DW), NSERC (JS, RAR, DW). This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».