Genetic mechanisms contributing to antimicrobial resistance: gene repression in Mycobacterium, gene transfer in Salmonella, and phage sensitivity in Escherichia
Notice bibliographique
Résumé
Bacteria develop resistance to antimicrobial agents through genetic mutation or horizontal acquisition of genetic material from resistant cells. Mycobacterium, Salmonella, and Escherichia are all capable of causing disease, and each demonstrates increasing resistance to conventional antibiotic treatment. Understanding the genetic mechanisms that regulate antibiotic resistance are critical in developing new antimicrobials and improving current treatment regimens. Alternative therapies to antibiotics should also be considered in the fight against multidrug resistant pathogens. Thus, I carried out molecular studies to investigate the regulation of efflux pump expression in Mycobacterium intracellulare, regulation mechanisms of natural competence in Salmonella Typhimurium, and phage therapy of Enterohemorrhagic Escherichia coli serogroup O157:H7. A recent study showed specific mutations in the uncharacterized locus mmpT5 increased resistance to anti-TB drug bedaquiline in M. intracellulare lung infections. Based on previous work, MmpT5 is a TetR transcription factor hypothesized to repress expression of the downstream Resistance Nodulation Division (RND) efflux pump mmpSL. To test this, we assembled multigene constructs on a plasmid with the modular cloning (MoClo) toolkit, which allowed us to control the expression of mmpT5 with the lacZ promoter and monitor mmpSL promoter activity with a fusion to lux. Consistent with the hypothesis, induction of mmpT5 reduced expression of mmpSL. The nonsynonymous mutations in mmpT5 first identified in clinical isolates resulted in upregulation of mmpSL, suggesting a mechanism for bedaquiline resistance. The periplasmic protein ComA is essential for active uptake of DNA from the environment. In Salmonella Typhimurium, comA is transcriptionally silent, even when the predicted activator Sxy is overexpressed. Identification of a mRNA stem-loop in the comA promoter region provides a possible gene repression mechanism. We used the MoClo toolkit to assemble comA promoter-luciferase fusions with or without the predicted mRNA secondary structure, and we used site-directed mutagenesis (SDM) to destabilize the predicted mRNA stem-loop. Luciferase reporter assays showed stem-loop removal or destabilization via SDM increased comA expression under the control of the lacZ promoter. SDM destabilization of the mRNA stem-loop did not increase luminescence of the native comA, but induction of sxy resulted in a 197-fold increase in luminescence compared to the wild type when the predicted stem-loop was destabilized, presenting a clear explanation for the cryptic nature of comA expression in Salmonella. Phage therapy presents an attractive alternative to conventional antibiotic treatment, prompting a study of the sensitivity of Enterohemorrhagic Escherichia coli (EHEC) serogroup O157:H7 to phage killing using a tetrazolium reduction assay. Measuring tetrazolium reduction at A485 successfully showed which EHEC strains were sensitive to the T4-like typing phage 13 (TP13). Addition of T7-like phage TP9 to TP13 increased the efficacy of phage treatment. TP13 resistance was observed in EHEC strains with the stx2a lysogen. RT-qPCR and plasmid complementation experiments showed that the hypothetical gene H2 was not responsible for TP13 resistance. Subsequent review of recent literature revealed that the downstream tyrosine kinase stk is likely responsible for TP13 resistance through abortive infection. Altogether, this thesis studies three bacterial systems to better understand the genetic bases of antimicrobial resistance, including gene transfer mechanisms, and to find the genetic bases of phage sensitivity.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 tête enseignante, 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 ».