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Antimicrobial resistance prediction and phylogenetic analysis of Neisseria gonorrhoeae isolates using the Oxford Nanopore MinION sequencer
Örebro University, School of Medical Sciences. WHO Collaborating Centre for Gonorrhoea and other Sexually Transmitted Infections, Department of Laboratory Medicine, Clinical Microbiology.ORCID iD: 0000-0002-0688-2521
Institute for Infectious Diseases, University of Bern, Bern, Switzerland; Institute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
Pathogen Genomics, The Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.
WHO Collaborating Centre for Gonorrhoea and other Sexually Transmitted Infections, Department of Laboratory Medicine, Clinical Microbiology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
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2018 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 8, no 1, article id 17596Article in journal (Refereed) Published
Abstract [en]

Antimicrobial resistance (AMR) in Neisseria gonorrhoeae is common, compromising gonorrhoea treatment internationally. Rapid characterisation of AMR strains could ensure appropriate and personalised treatment, and support identification and investigation of gonorrhoea outbreaks in nearly real-time. Whole-genome sequencing is ideal for investigation of emergence and dissemination of AMR determinants, predicting AMR, in the gonococcal population and spread of AMR strains in the human population. The novel, rapid and revolutionary long-read sequencer MinION is a small hand-held device that generates bacterial genomes within one day. However, accuracy of MinION reads has been suboptimal for many objectives and the MinION has not been evaluated for gonococci. In this first MinION study for gonococci, we show that MinION-derived sequences analysed with existing open-access, web-based sequence analysis tools are not sufficiently accurate to identify key gonococcal AMR determinants. Nevertheless, using an in house-developed CLC Genomics Workbench including de novo assembly and optimised BLAST algorithms, we show that 2D ONT-derived sequences can be used for accurate prediction of decreased susceptibility or resistance to recommended antimicrobials in gonococcal isolates. We also show that the 2D ONT-derived sequences are useful for rapid phylogenomic-based molecular epidemiological investigations, and, in hybrid assemblies with Illumina sequences, for producing contiguous assemblies and finished reference genomes.

Place, publisher, year, edition, pages
Nature Publishing Group, 2018. Vol. 8, no 1, article id 17596
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Bioinformatics and Computational Biology
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URN: urn:nbn:se:oru:diva-70622DOI: 10.1038/s41598-018-35750-4ISI: 000452084600004PubMedID: 30514867Scopus ID: 2-s2.0-85057604734OAI: oai:DiVA.org:oru-70622DiVA, id: diva2:1269373
Note

Funding Agencies:

Orebro County Council Research Committee  

Foundation for Medical Research at Orebro University Hospital, Orebro, Sweden  

SwissTransMed initiative (Translational Research Platforms in Medicine) from the Rectors' Conference of the Swiss Universities (CRUS)  25/2013 

Pathogen Informatics Group at the Wellcome Sanger Institute  

Wellcome Grant  098051 

Available from: 2018-12-10 Created: 2018-12-10 Last updated: 2025-02-07Bibliographically approved

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Golparian, DanielUnemo, Magnus

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