Antimicrobial susceptibility testing is therefore now central to the treatment of serious bacterial infections diagnosed by culture, and is used to determine the protocols for first-line antibiotic use when culture is not available. Clinical isolates resistant to most drugs have now been seen for many species including Mycobacterium tuberculosis, Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Neisseria gonorrhoeae, Acinetobacter baumannii and Pseudomonas aeruginosa 1. The marked increase in antibiotic use in health care and agriculture since the 1940s has driven a rise in frequency of drug-resistant bacterial strains, which now present a global threat to public health. 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. 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. 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). 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. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. 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.
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