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Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis

Abstract:
The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package ('Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/ncomms10063

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
NDM Experimental Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author


More from this funder
Funding agency for:
Peto, T
Crook, D
Grant:
Senior Investigator Award
Senior Investigator Award
G0800778
More from this funder
Funding agency for:
Wilson, D
Iqbal, Z
Grant:
101237/Z/13/Z
102541/Z/13/Z
More from this funder
Funding agency for:
Earle, S
Grant:
funded prize studentship to the Nuffield Department of Medicine
More from this funder
Funding agency for:
Bradley, P
McVean, G
Grant:
PhD studentship
100956/Z/13/Z
UK Clinical Research Collaboration 087646/Z/08/Z
Core Award Grant Number 090532/Z/09/Z


Publisher:
Nature Publishing Group
Journal:
Nature Communications More from this journal
Volume:
6
Pages:
10063-10063
Publication date:
2015-12-21
Acceptance date:
2015-10-28
DOI:
EISSN:
2041-1723


Pubs id:
pubs:581535
UUID:
uuid:0ab1313e-cb99-43e4-8fde-c3a0b7331d3f
Local pid:
pubs:581535
Source identifiers:
581535
Deposit date:
2016-01-12

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