Dataset Information

Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination.

ABSTRACT: 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.

SUBMITTER: Bhattacharyya RP

PROVIDER: S-EPMC6930013 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination.

Bhattacharyya Roby P RP Bandyopadhyay Nirmalya N Ma Peijun P Son Sophie S SS Liu Jamin J He Lorrie L LL Wu Lidan L Khafizov Rustem R Boykin Rich R Cerqueira Gustavo C GC Pironti Alejandro A Rudy Robert F RF Patel Milesh M MM Yang Rui R Skerry Jennifer J Nazarian Elizabeth E Musser Kimberly A KA Taylor Jill J Pierce Virginia M VM Earl Ashlee M AM Cosimi Lisa A LA Shoresh Noam N Beechem Joseph J Livny Jonathan J Hung Deborah T DT

Nature medicine 20191125 12

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 cli ...[more]

PMID: 31768064

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Project description:The emergence and prevalence of novel plasmid-mediated tigecycline resistance genes, namely, tet(X) and their variants, pose a serious threat to public health worldwide. Rapid and accurate antibiotic susceptibility testing (AST) that can simultaneously detect the genotype and phenotype of tet(X)-positive bacteria may contribute to the deployment of an effective antibiotic arsenal, mortality reduction, and a decrease in the use of broad-spectrum antimicrobial agents. However, current bacterial growth-based AST methods, such as broth microdilution, are time consuming and delay the prompt treatment of infectious diseases. Here, we developed a rapid RNA-based AST (RBAST) assay to effectively distinguish tet(X)-positive and -negative strains. RBAST works by detecting specific mRNA expression signatures in bacteria after short-term tigecycline exposure. As a proof of concept, a panel of clinical isolates was characterized successfully by using the RBAST method, with a 3-h assay time and 87.9% accuracy (95% confidence interval [CI], 71.8% to 96.6%). Altogether, our findings suggest that RNA signatures upon antibiotic exposure are promising biomarkers for the development of rapid AST, which could inform early antibiotic choices. IMPORTANCE Infections caused by multidrug-resistant (MDR) Gram-negative pathogens are an increasing threat to global health. Tigecycline is one of the last-resort antibiotics for the treatment of these complicated infections; however, the emergence of plasmid-encoded tigecycline resistance genes, namely, tet(X), severely diminishes its clinical efficacy. Currently, there is a lack of rapid and accurate antibiotic susceptibility testing (AST) for the detection of tet(X)-positive bacteria. In this study, we developed a rapid and robust RNA-based antibiotic susceptibility determination (RBAST) assay to effectively distinguish tet(X)-negative and -positive strains using specific RNA biomarkers in bacteria after tigecycline exposure. Using this RBAST method, we successfully characterized a set of clinical strains in 3 h. Our data indicate that the RBAST assay is useful for identifying tet(X)-positive Escherichia coli.

Dataset Information

Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination.

Publications

Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination.

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