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Primer relevamiento y caracterización de los mecanismos de resistencia a fluoroquinolonas (FQ) circulantes en Latinoamérica y desarrollo de una prueba de tamizaje para la detección de sensibilidad disminuida a FQ en aislamientos de Salmonella Entérica

2024· article· es· W7113193256 sur OpenAlexaboutno aff

Notice bibliographique

RevueRepositorio Digital Institucional de la Universidad de Buenos Aires (Universidad de Buenos Aires) · 2024
Typearticle
Languees
DomaineAgricultural and Biological Sciences
ThématiqueSalmonella and Campylobacter epidemiology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDNA gyraseSalmonella entericaNalidixic acidSalmonellaCiprofloxacinFosfomycinAntibiotic resistanceSerotype
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Salmonella, belonging to the Enterobacterales family, is responsible for infections with high morbidity and mortality worldwide. S. enterica is classified into non-typhoidal, which causes gastroenteritis, while typhoidal, restricted to humans, can cause typhoid fever with a mortality rate of up to 30% without treatment. It is estimated that S. enterica causes approximately 100 million infections and over 200,000 deaths annually, with 85% of cases linked to the consumption of animal-derived foods.\nFluoroquinolones (FQ) are broad-spectrum antibiotics that inhibit the DNA gyrase and topoisomerase IV enzymes, essential for bacterial replication. They are effective against Gram-negative bacteria, such as Salmonella and Escherichia coli, and some Gram-positive bacteria. Their extensive use in Salmonella infections has increased resistance, leading to therapeutic failures. The cut-off points established by guidelines like CLSI do not always adequately detect resistance mechanisms, such as mutations in gyrA, parC, and the presence of qnr, underestimating resistance. This has highlighted the need to adjust the cut-off points to improve diagnostic accuracy and ensure effective treatments.\nGiven this background, this doctoral thesis aims to: (a) characterize the FQ resistance mechanisms in Salmonella spp. from different regions of Latin America and their distribution, and (b) develop a rapid and accessible screening test to detect decreased FQ susceptibility in S. enterica isolates.\nA total of 334 isolates from 16 countries in Latin America and Canada, collected between December 2012 and July 2013 through ReLAVRA, were studied. Serotypes were identified, and antimicrobial susceptibility tests were performed using standardized methodologies. Strains with inhibition zones for ciprofloxacin (CIP) ?30 mm or nalidixic acid (NAL) ?21 mm were included. Susceptibility to ciprofloxacin (CIP), nalidixic acid (NAL), norfloxacin (NOR), pefloxacin (PEF), levofloxacin (LEV), and pipemidic acid (PI) was evaluated, along with the phenotypic-genotypic correlation using MIC50, MIC90, geometric mean, and range. Genomes of isolates with discrepancies were sequenced and analyzed using open-access bioinformatics programs. The diagnostic accuracy of phenotypic tests was determined by calculating sensitivity, specificity, and predictive values using CLSI cut-off points and alternative ones where CLSI guidelines were unavailable.\nOf the 17 participating countries, 12 sent between 20 and 25 isolates, while the remaining sent between 8 and 17. The most frequent serotypes were S. Enteritidis, S. Typhimurium, and S. Typhi, representing 73% of the total sample. The analysis of quinolone resistance genes showed that 25% of the isolates exhibited a wild-type phenotype. Among the remaining 75%, gyrA mutations were the most frequent (39.5%, 132/334), followed by qnr (22%, 74/334). Three percent of the strains had gyrB mutations, and 11% showed combinations of mechanisms. MIC50 and MIC90 analyses showed that the described resistance mechanisms did not cause significant increases in MICs for FQs such as LEV and CIP, varying from moderate to low. gyrA mutations increased NAL MICs over 100-fold, while qnr caused less than a 10-fold increase, with no significant changes in CIP and LEV. The accumulation of mechanisms led to high resistance levels (MIC50 of 0.5 ?g/ml and MIC90 of 8 ?g/ml for CIP), especially for NAL (MICs >256 ?g/ml).\nThe most common amino acid change in gyrA was D87N, followed by S83F and S83Y. In gyrB, 10 isolates showed unique mutations (L451F, Q465L, S464F). Regarding Qnr proteins, qnrB (96.6%) and qnrS (3.4%) were identified. The NAL disk was the most efficient for distinguishing strains with gyrA mutations from wild-type strains. gyrB mutations affected the phenotype variably, without a specific quinolone discriminating well between them. For qnr, the NAL disk performed well but may not be recommended in regions with high prevalence of qnrS. NAL inhibition zones ?17 mm and PI ?16 mm allowed the distinction of all wild-type isolates from those with DNA gyrase mutations combined with qnrB, qnrS, oqxAB, etc. Overall, the NAL (30 ?g) disk with a cut-off point of 22 mm is the most suitable for laboratories in the Americas, given its superior performance in the region.\nThe complete genome sequencing of 17 isolates helped to understand the discrepancies between phenotype and genotype, confirming the species and serovar of each isolate. Three S. Enteritidis were identified as ST11 and seven of eight S. Typhi as ST2, while other isolates presented various STs. WGS corroborated the genotype detected by PCR and Sanger in cases with high MICs, where the phenotype was explained by the sum of mechanisms. In other cases, a mutation in gyrB (S464F) and the absence of additional mechanisms were confirmed. The qnrB19 allele was detected in isolates from four countries, indicating its wide distribution. As a finding, mcr-5 was identified in an S. Typhimurium ST19 isolate from Colombia.\nThe data obtained were shared with the CLSI Subcommittee on Susceptibility Testing, contributing to the update of screening methods and breakpoints for fluoroquinolones in Salmonella. Additionally, they had an immediate impact as ReLAVRA+ used them to improve the diagnostic strategies for AMR in Salmonella in the region, enhancing resistance detection, patient management, and strengthening One Health surveillance systems in Latin America.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Études des sciences et des technologies, Communication savante, Intégrité de la recherche
Catégories consensuellesMéta-épidémiologie (sens strict)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,613
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0030,001
Science ouverte0,0020,001
Intégrité de la recherche0,0030,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,265
Écart entre enseignants0,256 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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