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

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.

SUBMITTER: Hicks AL

PROVIDER: S-EPMC7326491 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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

Hicks Allison L AL Kissler Stephen M SM Mortimer Tatum D TD Ma Kevin C KC Taiaroa George G Ashcroft Melinda M Williamson Deborah A DA Lipsitch Marc M Grad Yonatan H YH

eLife 20200630

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 targe ...[more]

PMID: 32602459

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Project description:Emerging known and unknown pathogens create profound threats to public health. Platforms for rapid detection and characterization of microbial agents are critically needed to prevent and respond to disease outbreaks. Available detection technologies cannot provide broad functional information about known and novel organisms. As a step toward developing such a system, we have produced and tested a series of high-density functional gene arrays to detect elements of virulence and antibiotic resistance mechanisms. Our first generation array targets genes from Escherichia coli strains K12 and CFT073, Enterococcus faecalis and Staphylococcus aureus. We determined optimal probe design parameters for gene family detection and discrimination. When tested with organisms at varying phylogenetic distances from the four target strains, the array detected orthologs for the majority of targeted gene families present in bacteria belonging to the same taxonomic family. In combination with whole-genome amplification, the array detects femtogram concentrations of purified DNA, either spiked in to an aerosol sample background, or in combinations from one or more of the four target organisms. This is the first report of a high density NimbleGen microarray system targeting microbial antibiotic resistance and virulence mechanisms. By targeting virulence gene families as well as genes unique to specific biothreat agents, these arrays will provide important data about the pathogenic potential and drug resistance profiles of unknown organisms in environmental samples. Keywords: detection, pathogen, virulence mechanism In this report, we describe the process used to design our first generation functional array for highly sensitive detection of virulence and antibiotic resistance gene families. We discuss the probe design algorithms, including virulence gene sequence selection, and our protocols for sample preparation, amplification, labeling, hybridization, and data analysis. We present the results from experiments designed to assess whether the array can detect virulence gene orthologs from organisms without perfect match probes on the array, using both targeted mismatch probes and hybridizations to DNA from other organisms. Also, we report the results from limit of detection studies, using known amounts of bacterial DNA spiked into aerosol samples to measure the minimal concentration required for detection of virulence elements against a complex background.

Dataset Information

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

Publications

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

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