Rapid inference of antibiotic resistance and susceptibility by genomic neighbour typing

Brinda, Karel, Callendrello, Alanna, Ma, Kevin C., MacFadden, Derek R., Charalampous, Themoula, Lee, Robyn S., Cowley, Lauren, Wadsworth, Christa B., Grad, Yonatan H., Kucherov, Gregory, O'Grady, Justin, Baym, Michael and Hanage, William P. (2020) Rapid inference of antibiotic resistance and susceptibility by genomic neighbour typing. Nature Microbiology, 5 (3). pp. 455-464. ISSN 2058-5276

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Abstract

Genomic neighbour typing can be used to infer the antimicrobial susceptibility and resistance of a bacterial sample based on the genomes of closest relatives. Combined with MinION sequencing, it can rapidly determine microbial resistance for clinical samples within 4 h. Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empirical antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could affect patient treatment and outcomes. Here, we present a method called 'genomic neighbour typing' for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata. We show that this technique can infer antibiotic susceptibility and resistance for both Streptococcus pneumoniae and Neisseria gonorrhoeae. We implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION data, can run in real time. This resulted in the determination of resistance within 10 min (91% sensitivity and 100% specificity for S. pneumoniae and 81% sensitivity and 100% specificity for N. gonorrhoeae from isolates with a representative database) of starting sequencing, and within 4 h of sample collection (75% sensitivity and 100% specificity for S. pneumoniae) for clinical metagenomic sputum samples. This flexible approach has wide application for pathogen surveillance and may be used to greatly accelerate appropriate empirical antibiotic treatment.

Item Type: Article
Uncontrolled Keywords: streptococcus-pneumoniae,united-states,genes,identification,epidemiology,surveillance,clones,tool,applied microbiology and biotechnology,microbiology (medical),genetics,cell biology,microbiology,immunology ,/dk/atira/pure/subjectarea/asjc/2400/2402
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
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Depositing User: LivePure Connector
Date Deposited: 07 Dec 2019 02:22
Last Modified: 31 Mar 2020 00:41
URI: https://ueaeprints.uea.ac.uk/id/eprint/73298
DOI: 10.1038/s41564-019-0656-6

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