Exploring the relationship between bacterial genera and lipid metabolism in bovine rumen
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
The rumen is characterised by a complex microbial ecosystem, which is particularly active in lipid metabolism. Several studies demonstrated a role of diet and breed on bacterial community profile, with the effect on metabolic pathways. Despite the knowledge achieved on metabolism and the bacterial profile, little is known about the relationship between individual bacteria and metabolic pathways. Therefore, a multivariate approach was used to search for possible relationships between bacteria and products of several pathways. The correlation between rumen bacterial community composition and rumen lipid metabolism was assessed in 40 beef steers (20 Maremmana and 20 Aubrac) reared with the same system and fed the same diet. A canonical discriminant analysis combined with a canonical correlation analysis (CCA) was performed to explore this correlation. The variables showing a Pearson correlation higher than 0.6 as absolute value and significant were retained for CCA considering the relationship of bacterial composition with several metabolic pathways. The results indicated that some bacterial genera could have significant impacts on the presence of several fatty acids. However, the relationship between genera and fatty acid changes according to the breed, demonstrating that the metabolic pathways change according to the host genetic background, related to breed evolution, although there is also an intra-breed genetic background which should not be ignored. In Maremmana, Succiniclasticum and Rikenellaceae_RC9_gut_group showed a high positive correlation with dimethylacetals (DMAs) DMAC13:0, DMAC14:0, DMAC14:0iso, DMAC15:0, DMAC15:0iso, and DMAC18:0. Prevotellaceae_UCG-003 correlates with C18:3c9c12c15 and C18:1t11, while Fibrobacter and Succiniclasticum correlate with C18:2c9t11 and Lachnospiraceae_NK3A20_group correlates with C18:1c12. Prevotellaceae_UCG-003, Ruminococcaceae_UCG-010, and Oribacterium showed a positive correlation with C13:0iso, and C17:0. Conversely, in Aubrac, Treponema_2 and Rikenellaceae_RC9_gut_group correlated with DMAC14:0iso, DMAC16:0iso, DMAC17:0iso, while Ruminococcaceae_UCG-010, Christensenellaceae_R-7_group and Ruminococcaceae_NK4A214_group correlated with DMAC18:1t11, DMAC14:0, DMAC18:1c12. Acetitomaculum correlated with C18:2c9c12, C18:1c12, C18:1c13, C18:1t12 and Lachnospiraceae_NK3A20_group with C18:1t6-8 and C18:1t9. Saccharofermentas, Ruminococcaceae_UCG-010 and Rikenellaceae_RC9_gut_group correlated with C18:2c9t11 while, Prevotellaceae_UCG-001 and Ruminococcus_1 correlated with C14:0iso, C15:0, C15:0iso, C17:0. Saccharofermentans, Rikenellaceae_RC9_gut_group, Ruminococcaceae_NK4A214_group, and Ruminococcaceae_UCG-010 correlated with C13:1c12 and C16:0iso. These results lead to hypothesise a possible association between several metabolic pathways and one or a few bacterial genera. If these associations are confirmed by further investigations that verify the causality of a bacterial genus with a particular metabolic process, it will be possible to deepen the knowledge on the activity of the rumen population in lipid metabolism. This approach appears to be a promising tool for uncovering the correlation between bacterial genera and products of rumen lipid metabolism.
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.
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 découle