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1.
Nat Med ; 25(12): 1858-1864, 2019 12.
Artículo en Inglés | MEDLINE | ID: mdl-31768064

RESUMEN

Multidrug resistant organisms are a serious threat to human health1,2. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying multidrug resistant organisms increase mortality3,4 and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution5, require several days before informing key clinical decisions. Rapid AST would transform the care of patients with infection while ensuring that our antibiotic arsenal is deployed as efficiently as possible. Growth-based assays are fundamentally constrained in speed by doubling time of the pathogen, and genotypic assays are limited by the ever-growing diversity and complexity of bacterial antibiotic resistance mechanisms. Here we describe a rapid assay for combined genotypic and phenotypic AST through RNA detection, GoPhAST-R, that classifies strains with 94-99% accuracy by coupling machine learning analysis of early antibiotic-induced transcriptional changes with simultaneous detection of key genetic resistance determinants to increase accuracy of resistance detection, facilitate molecular epidemiology and enable early detection of emerging resistance mechanisms. This two-pronged approach provides phenotypic AST 24-36 h faster than standard workflows, with <4 h assay time on a pilot instrument for hybridization-based multiplexed RNA detection implemented directly from positive blood cultures.


Asunto(s)
Antibacterianos/farmacología , Farmacorresistencia Bacteriana/genética , Pruebas de Sensibilidad Microbiana , ARN Bacteriano/aislamiento & purificación , Antibacterianos/efectos adversos , Genotipo , Humanos , Aprendizaje Automático , Fenotipo , ARN Bacteriano/efectos de los fármacos
2.
Sci Rep ; 9(1): 4516, 2019 03 14.
Artículo en Inglés | MEDLINE | ID: mdl-30872641

RESUMEN

Rapid bacterial identification remains a critical challenge in infectious disease diagnostics. We developed a novel molecular approach to detect and identify a wide diversity of bacterial pathogens in a single, simple assay, exploiting the conservation, abundance, and rich phylogenetic content of ribosomal RNA in a rapid fluorescent hybridization assay that requires no amplification or enzymology. Of 117 isolates from 64 species across 4 phyla, this assay identified bacteria with >89% accuracy at the species level and 100% accuracy at the family level, enabling all critical clinical distinctions. In pilot studies on primary clinical specimens, including sputum, blood cultures, and pus, bacteria from 5 different phyla were identified.


Asunto(s)
Bacterias/clasificación , Hibridación de Ácido Nucleico/métodos , ARN Ribosómico 16S/genética , Bacterias/genética , Bacterias/aislamiento & purificación , Bacterias/patogenicidad , Mycobacterium/clasificación , Mycobacterium/genética , Mycobacterium/aislamiento & purificación , Mycobacterium/patogenicidad , Filogenia , Staphylococcus aureus/clasificación , Staphylococcus aureus/genética , Staphylococcus aureus/aislamiento & purificación , Staphylococcus aureus/patogenicidad
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