290 Impact of altering maternal gut microbiome via high-forage or high-concentrate diets on offspring microbiome development, methane emissions and animal performance in cattle.
Notice bibliographique
Résumé
Abstract Maternal gut microbiome has been shown to influence immune, metabolic and neurodevelopmental programming of offspring from the embryonic stage, suggesting a potential role in the Developmental Origins of Health and Disease (DOHaD). Whereas many still support the “sterile-womb hypothesis” that the neonatal microbiome acquisition occurs only during and after birth, very recent studies have provided evidence showing the existence of in utero microbial colonization. Thus, these recent developments in the field of microbiome research of human and vertebrate animals including bovine animals highlight that the maternal gut microbiome during pregnancy should be targeted for harnessing their extended impact on the offspring’s development and health. In this presentation, we will discuss the potential involvement of maternal microbiome and feto-maternal microbial crosstalk in fetal programming, and offspring calf’s health and development. In addition, we will discuss the results from our recently conducted longitudinal study focused on the evaluation of the impact of altering maternal microbiota via high forage or high concentrate diets on offspring microbiome development, energy balance, methane emissions and feedlot performance in beef cattle. For this, 120 beef heifers were assigned to one of two treatments and received a diet based on 75% forage (HF) or 75% concentrate (HC) from 15 days pre-breeding through calving. Heifers were bred using male-sexed semen and fed to target a gain of 0.45kg/d for both groups. Ruminal fluid, fecal and vaginal swabs were collected from both HF (n = 24) and HC (n =22) heifers on pre-breeding (-30, -2), post-breeding (56, 91, 180, and 238 days of gestation) and at calving. Calves born from these heifers were monitored for their animal performance, feed efficiency, gut microbiome development and enteric methane emission (in vitro and in vivo). Body weight measurements, ruminal fluid and fecal samples were collected from the calves at 0, 15, 30, 60, 120, 160, 240, 330 and 340 days old. The 16S rNRA gene sequencing was performed on the dam and calf’s microbiome samples. An in-vitro fermentation assay was performed on the ruminal fluid samples from heifers and their calves for methane and VFA analyses. During finishing stage, a subset of calves born from HF and HC dams (n = 10 each group) were evaluated to examine effects on energy metabolism, nutrient balance and enteric methane emission (using headbox) output between the HF and HC offspring because of the HF or HC diet their dams received during fetal development. The results from this study provide novel insights into the impact of altered maternal gut microbiome during pregnancy on the postnatal animal performance, feed efficiency, microbiome development and enteric methane emission phenotype in cattle.
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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) | 0,000 | 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) | 0,001 | 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 ».