188 Characterization of the Vagino-Uterine Microbiota in Pregnant and Non-Pregnant Beef Cattle Using 16S Rrna Gene Sequencing and Culturing
Notice bibliographique
Résumé
Abstract Emerging evidence suggests that urogenital microbiome-targeted approaches may provide a novel opportunity to reduce the incidence of reproductive failures in cattle. The objectives of this study were to: 1) characterize the vaginal and uterine microbiota between beef cattle that became pregnant via artificial insemination (AI) and those that did not; 2) identify differentially abundant taxa between pregnant and non-pregnant cattle; and 3) characterize the culturable fraction of the vaginal and uterine microbiota using extensive culturing. Vaginal and uterine swab samples were collected from two cohorts of Angus-crossbred cattle: mature cows (n =100) and heifers (n = 72, vaginal swab only) at the time of AI. At 35 days post-AI, pregnancy diagnoses were made via ultrasound. A subset of vaginal and uterine swabs from cows (27 non-pregnant and 31 pregnant) and heifers (26 non-pregnant and 33 pregnant) were selected and processed for microbiota assessment using 16S rRNA gene (V3-V4) sequencing. For culturing, a subset of cryopreserved vaginal and uterine swabs (128) were plated onto three different agar types and cultured, and isolates were identified by near-full length 16S rRNA gene sequencing. Sequencing results revealed 11 taxa that were more abundant in the vaginas of heifers that failed to become pregnant via AI than heifers that did become pregnant. While there was no significant difference in vaginal microbiota community structure (P = 0.21) between pregnant and non-pregnant cows, non-pregnant cows tended to have greater microbial richness and Shannon diversity (P ≤ 0.08) compared with pregnant cows. No differentially abundant taxa were detected in the vaginas of pregnant versus non-pregnant cows. Pregnant cows had a distinct uterine microbiota community structure (R2 = 0.032, P = 0.008) but similar alpha diversity (P > 0.1) compared with non-pregnant cows. Twenty-eight differentially abundant taxa were observed in the uterine microbiota between pregnant and non-pregnant groups, with 11 of them more abundant in pregnant cows. Methanobrevibacter ruminantium (archaea) and Fusobacterium necrophorum were among these 11 positive pregnancy-associated taxa. Although community structure was significantly different between the vagina and uterus, 277 “core taxa” (present in ≥ 80% of all samples) were shared between the two communities. A total of 733 bacterial isolates were recovered from vaginal (512) and uterine (221) swabs under aerobic (n = 363, 83 different species) and anaerobic (n = 370, 69 species) culturing. Potential pathogenic isolates within the Trueperella, Mannheimia and Histophilus genera were most exclusively identified from vaginal swabs. Only two Lactobacillus isolates were recovered. Overall, our results indicate that pregnancy-associated taxonomic signatures are present in the bovine uterine and vaginal microbiota. Among 39 pregnancy status-associated taxa, 41% were unclassified at the genus level, suggesting that shotgun metagenomics and culturomics are needed to identify and characterize the pregnancy-associated taxa in cattle.
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) | 0,000 | 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 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 ».