Interactions of the Hindgut Mucosa-Associated Microbiome with Its Host Regulate Shedding of Escherichia coli O157:H7 by Cattle
Notice bibliographique
Résumé
ABSTRACT Cattle are the primary carrier of Escherichia coli O157:H7, a foodborne human pathogen, and those shedding >10 4 CFU/gram of feces of E. coli O157:H7 are defined as supershedders (SS). This study investigated the rectoanal junction (RAJ) mucosa-associated microbiota and its relationship with host gene expression in SS and in cattle from which E. coli O157:H7 was not detected (nonshedders [NS]), aiming to elucidate the mechanisms involved in supershedding. In total, 14 phyla, 66 families, and 101 genera of RAJ mucosa-associated bacteria were identified and Firmicutes (61.5 ± 7.5%), Bacteroidetes (27.9 ± 6.4%), and Proteobacteria (5.5 ± 2.1%) were the predominant phyla. Differential abundance analysis of operational taxonomic units (OTUs) identified 2 OTUs unique to SS which were members of Bacteroides and Clostridium and 7 OTUs unique to NS which were members of Coprococcus , Prevotella , Clostridium , and Paludibacter . Differential abundance analysis of predicted microbial functions (using PICRUSt [phylogenetic investigation of communities by reconstruction of unobserved states]) revealed that 3 pathways had higher abundance (log 2 fold change, 0.10 to 0.23) whereas 12 pathways had lower abundance (log 2 fold change, −0.36 to −0.20) in SS. In addition, we identified significant correlations between expression of 19 differentially expressed genes and the relative abundance of predicted microbial functions, including nucleic acid polymerization and carbohydrate and amino acid metabolism. Our findings suggest that differences in RAJ microbiota at both the compositional and functional levels may be associated with E. coli O157:H7 supershedding and that certain microbial groups and microbial functions may influence RAJ physiology of SS by affecting host gene expression. IMPORTANCE Cattle with fecal E. coli O157:H7 at >10 4 CFU per gram of feces have been defined as the supershedders, and they are responsible for the most of the E. coli O157:H7 spread into farm environment. Currently, no method is available for beef producers to eliminate shedding of E. coli O157:H7 in cattle, and the lack of information about the mechanisms of supershedding greatly impedes the development of effective methods. This study investigated the role of the rectoanal junction (RAJ) mucosa-associated microbiome in E. coli O157:H7 shedding, and our results indicated that the compositions and functions of RAJ microbiota differed between supershedders and nonshedders. The identified relationship between the differentially abundant microbes and 19 previously identified differentially expressed genes suggests the role of host-microbial interactions involved in E. coli O157:H7 supershedding. Our findings provide a fundamental understanding of the supershedding phenomenon which is essential for the development of strategies, such as the use of directly fed microbials, to reduce E. coli O157:H7 shedding 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 | 0,001 | 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 ».