A202 ROLE OF EXTRACELLULAR VESICLES IN <i>GIARDIA</i>-MICROBIOTA INTERACTIONS.
Notice bibliographique
Résumé
Abstract Background Extracellular vesicles (EVs) have emerged as important mediators of host-parasite interactions. Studies in various parasites have shown that EVs have important roles in pathogenesis. The protozoan parasite Giardia duodenalis, which causes diarrheal disease, produces EVs in response to changes in the environment. However, their exact role in the pathogenesis of giardiasis remains unclear. In this study, we investigate the effects of Giardia EVs on the gut commensal bacteria. EVs mediated disruption of the microbiota represents a novel mechanism that has not been investigated before. Aims We hypothesize that Giardia EVs contain virulence factors that will modify the growth and behavior of commensal bacteria. Based on our hypothesis, the study has three aims: 1. Quantify and characterize the EVs produced by Giardia under varying conditions. 2. Examine the effects of Giardia EVs on commensal bacteria. 3. Identify proteins and virulence factors in Giardia EVs using proteomics. Methods G. duodenalis (isolate NF) was exposed to bile or left untreated and the EVs were isolated using Exo-Easy Maxi Kit (Qiagen). The isolated EVs were characterized using Nanosight track analysis (NTA) and transmission electron microscopy. To examine the effects of EVs on bacteria, we used a lab strain E.coli HB101 and human isolate E. cloacae. The bacteria were incubated with Giardia EVs and their growth rate was monitored using a bacterial kinetics assay. The swimming motility of bacteria exposed to Giardia EVs was assessed on a 0.3% agar. Additionally, the ability of the EVs treated bacteria to adhere to epithelial cells was also examined. Proteomic analysis of EVs was conducted using liquid chromatography with tandem mass spectrometry. Results Results indicate that bile treated Giardia trophozoites produce more EVs as compared to untreated trophozoites. Giardia EVs exerted bacteriostatic effects on E.coli HB101 and E. cloacae. Additionally, Giardia EVs significantly increased the swimming motility of both E.coli HB101 and E. cloacae as well as their adhesion to the intestinal epithelial cells. Finally, proteomic analysis of EVs revealed the presence of well-characterized Giardia virulence factors such as cysteine proteases, tenascins, variant surface proteins as well as metabolic enzymes such as arginine deaminase and ornithine carbamoyltransferase. Conclusions Our research highlights a novel mechanism of Giardia’s interaction with commensal bacteria. Our results indicate that Giardia can release EVs in response to changes in the environment. These EVs also contain virulence factors that can modify the growth and behavior of commensal bacteria. These effects may have significant implications in disease pathophysiology. The results of the study can also be applied to other parasitic diseases where the production of EVs has been shown to play a role in the pathogenesis process. Funding Agencies NSERC
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 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».