191 Evaluating the Efficacy of Lactobacilli-Based Direct-Fed Microbials (DFM) in reducing Shiga-toxigenic Escherichia coli (STEC) O157:H7 colonization using cell and tissue culture models.
Notice bibliographique
Résumé
Abstract Background: STEC O157:H7 is a major global food safety and public health concern, with cattle serving as the primary reservoir. Colonization of STEC O157 in the cattle gastrointestinal tract, particularly the terminal rectum, leads to beef contamination and causing frequent outbreaks. Effective on-farm interventions are essential to reduce STEC transmission. Direct-Fed Microbials (DFMs) are live microorganisms, including beneficial bacteria or yeast, that are directly administered to animals to enhance gut health, reduce pathogenic load, and improve overall performance. Among 14 DFM candidates screened in our previous study, Ligilactobacillus agilis strains L3 and L6 showed the highest in vitro antimicrobial activity, making them promising candidates for reducing STEC O157 colonization. However, there is limited research on their efficacy in reducing STEC O157 attachment to intestinal epithelial cells and tissues. Objective: This study evaluates the potential of L. agilis DFM strains L3 and L6 to reduce STEC O157 colonization using in vitro cell (cattle ileum epithelial cells) and cattle tissue (terminal rectum) culture models. Methodology: STEC O157 strains R508N and R318N were used. Cattle ileum epithelial cells were isolated via enzymatic digestion and mechanical scraping, followed by purification and culture. Terminal rectum tissue cultures were prepared from fresh cattle intestinal tissues. For the attachment assay, epithelial cells were seeded in 24-well plates and exposed to STEC O157 suspensions. Tissue pieces (2.5 cm²) were inoculated with STEC O157 (10⁶ CFU) and incubated for 4 hours. Bacterial adherence was quantified by lysing cells or tissues, followed by plating and colony counting. L. agilis strains L3 and L6 will be applied to these models to assess their ability to reduce STEC colonization. Results: Preliminary results showed STEC O157 effectively colonized both cell and tissue cultures, with attachment levels ranging from 10⁶ to 10⁷ CFU. The next phase involves applying DFM (L3 and L6) to cell and tissue culture models to evaluate their ability to inhibit STEC O157 colonization. The attachment assay will assess DFM impact on STEC attachment to epithelial cells, while tissue models will evaluate colonization reduction in the terminal rectum. The goal is to identify DFM formulations that effectively inhibit STEC colonization, providing a potential intervention strategy for reducing pathogen load in cattle. Conclusions and Expected Outcomes: The expected outcomes of this study include demonstrating the ability of L3 and L6 to reduce STEC O157 attachment to epithelial cells and terminal rectum tissues. By investigating the interactions between STEC O157, DFMs, and the host, this research will provide mechanistic insights that contribute to the development of effective strategies for controlling this pathogen in cattle and mitigating its transmission to humans. The application of L. agilis DFMs shows promising potential in reducing STEC colonization, thereby enhancing food safety and improving public health outcomes.
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 | 0,001 |
| 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».