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Targeted surveillance strategies for efficient detection of novel antibiotic resistance variants.

Published version
Peer-reviewed

Type

Article

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Authors

Ma, Kevin C 
Taiaroa, George 

Abstract

Genotype-based diagnostics for antibiotic resistance represent a promising alternative to empiric therapy, reducing inappropriate antibiotic use. However, because such assays infer resistance based on known genetic markers, their utility will wane with the emergence of novel resistance. Maintenance of these diagnostics will therefore require surveillance to ensure early detection of novel resistance variants, but efficient strategies to do so remain undefined. We evaluate the efficiency of targeted sampling approaches informed by patient and pathogen characteristics in detecting antibiotic resistance and diagnostic escape variants in Neisseria gonorrhoeae, a pathogen associated with a high burden of disease and antibiotic resistance and the development of genotype-based diagnostics. We show that patient characteristic-informed sampling is not a reliable strategy for efficient variant detection. In contrast, sampling informed by pathogen characteristics, such as genomic diversity and genomic background, is significantly more efficient than random sampling in identifying genetic variants associated with resistance and diagnostic escape.

Description

Keywords

Neisseria gonorrhoeae, antibiotic resistance, diagnostic, epidemiology, global health, infectious disease, microbiology, surveillance, Anti-Bacterial Agents, Drug Resistance, Bacterial, Genome, Bacterial, Gonorrhea, Neisseria gonorrhoeae

Journal Title

Elife

Conference Name

Journal ISSN

2050-084X
2050-084X

Volume Title

9

Publisher

eLife Sciences Publications, Ltd