Nano-enabled Antibacterial Combination Therapy (NeACT) Targeting Intracellular Salmonella enterica ser. Typhimurium to Treat Intestinal Infections in Swine
Notice bibliographique
Résumé
Salmonellosis is a zoonotic infection caused by gram-negative Salmonella spp. and is amongst the top four bacterium causing foodborne infections globally. Transmission generally occurs through animal-based food such as pork. There exist many Salmonella enterica. serovars and S. Typhimurium (ST) has shown a global prevalence. Furthermore, ST infections pose a significant threat to the swine industry due to reduced production, lack of treatment, economic losses, etc. The prevalence of the infection and the rise of antimicrobial resistance (AMR) in livestock warrants intervention strategies that can reduce and treat infection. This thesis research focused on two main aspects: (1) determination of the phenotypic and genotypic profile of a swine Salmonella enterica ser. Typhimurium isolate obtained from an animal farm in Quebec for extreme drug resistance, and (2) developing a Nano-enabled Antibacterial Combination Therapy to eliminate intracellular pathogenesis of multidrug-resistance (MDR) Salmonella enterica ser. Typhimurium.The first phase of this study consisted of the phenotypic and genotypic study of the swine Salmonella enterica ser. Typhimurium isolate from a Quebec animal farm. The isolate was characterized for its AMR genes using whole genome sequencing (WGS) where resistance to more than 8 antibiotic classes was identified. Generally, the WGS data validated the phenotypic results. The WGS data predicted genes aph(6)-Id and aph(3'')-Ib to confer resistance to streptomycin alone, however, resistance was phenotypically observed with streptomycin as well. This is a result of the two belonging to the same antibiotic group: aminoglycosides and having similar modes of action. Furthermore, we investigated their intracellular infection in an in vitro swine epithelial intestinal model, IPEC-J2 cells. Remarkably, the antibiotics reported to be effective against ST, when tested were unsuccessful in remediating intracellular infection in IPEC-J2 cells. Consequently, alternate and novel treatments are required to target this multi-drug resistance (MDR) intracellular pathogen. Combination therapy was sought as a solution to repurpose antibiotics and polyphenols because of their accessibility and their use in the swine industry. Accordingly, the first part of thesis addresses assessing the effectiveness of antibiotic-adjuvant combinations for eliminating MDR ST. Studies conducted using checkerboard assay and identifying antibacterial synergism using their fractional inhibitory concentration index (FICI) revealed, amoxicillin (AMOX) and tazobactam (TAZO) to be the best combination among the tested molecules and was therefore selected for further analysis. The above combination was further encapsulated in a cyclodextrin (CD) and liposome (LP) as the selected nano-carriers for their drug delivery abilities. The final drug, LP-CAT was of 232.34±4.76 nm in size and exhibited surface charge of -41.87±5.11 mV. The encapsulation efficiency was determined spectrophotometrically, AMOX and TAZO was found to be 46.5±1.11% and 49±1.79% respectively. LP-CAT showed improved antibacterial efficiency and the ability to reduce intracellular pathogenicity against ST in IPEC-J2 cells. The results of this study highlight the potential of LP-CAT (NeACT) as an alternative to target intracellular pathogens in animal agriculture
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) | 0,001 | 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 ».