Rapid inference of antibiotic resistance and susceptibility by genomic neighbour typing.

Autor: Břinda K; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. kbrinda@hsph.harvard.edu.; Department of Biomedical Informatics and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA. kbrinda@hsph.harvard.edu., Callendrello A; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA., Ma KC; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA., MacFadden DR; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA.; Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Ontario, Canada., Charalampous T; Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, UK., Lee RS; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA.; Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada., Cowley L; Department of Biology and Biochemistry, University of Bath, Bath, UK., Wadsworth CB; Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY, USA., Grad YH; Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA., Kucherov G; CNRS/LIGM Université Paris-Est, Marne-la-Vallée, France.; Skolkovo Institute of Science and Technology, Moscow, Russia., O'Grady J; Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, UK.; Quadram Institute Bioscience, Norwich Research Park, Norwich, UK., Baym M; Department of Biomedical Informatics and Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA., Hanage WP; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Jazyk: angličtina
Zdroj: Nature microbiology [Nat Microbiol] 2020 Mar; Vol. 5 (3), pp. 455-464. Date of Electronic Publication: 2020 Feb 10.
DOI: 10.1038/s41564-019-0656-6
Abstrakt: 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.
Databáze: MEDLINE
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