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Purpose Speed of bloodstream infection diagnosis is vital to reduce morbidity and mortality. Whole genome sequencing (WGS) performed directly from liquid blood culture could provide single-assay species and antibiotic susceptibility prediction; however, high inhibitor and human cell/DNA concentrations limit pathogen recovery. We develop a method for the preparation of bacterial DNA for WGS-based diagnostics direct from liquid blood culture. Methodology We evaluate three commercial DNA extraction kits: BiOstic Bacteraemia, Amplex Hyplex and MolYsis Plus. Differential centrifugation, filtration, selective lysis and solid-phase reversible immobilization bead clean-up are tested to improve human cells/DNA and inhibitor removal. Using WGS (Illumina/MinION), we assess human DNA removal, pathogen recovery, and predict species and antibiotic susceptibility inpositive blood cultures of 44 Gram-negative and 54 Staphylococcus species. Results/Key findings BiOstic kit extractions yield the greatest mean DNA concentration, 94–301 ng µl−1, versus 0–2.5 ng µl−1 using Amplex and MolYsis kits. However, we note higher levels of inhibition (260/280 ratio 0.9–2.1) and human DNA (0.0–4.4×106 copies) in BiOstic extracts. Differential centrifugation (2000 g, 1 min) prior to BiOstic extraction reduces human DNA by 63–89 % with selective lysis minimizing by a further 62 %. Post-extraction bead clean-up lowers inhibition. Overall, 67 % of sequenced samples (Illumina MiSeq) contain 93 % concordance between WGS-based species and susceptibility predictions and clinical diagnosis. If >60 % of sequencing reads are human (7/98 samples) susceptibility prediction becomes compromised. Novel MinION-based WGS (n=9) currently gives rapid species identification but not susceptibility prediction. Conclusion Our method for DNA preparation allows WGS-based diagnosis direct from blood culture bottles, providing species and antibiotic susceptibility prediction in a single assay.

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., The clinical application of new sequencing techniques is expected to accelerate pathogen identification. Here, Bradley et al. present a clinician-friendly software package that uses sequencing data for quick and accurate prediction of antibiotic resistance profiles for S. aureus and M. tuberculosis.

Colistin represents one of the few available drugs for treating infections caused by carbapenem-resistant Enterobacteriaceae. As such, the recent plasmid-mediated spread of the colistin resistance gene mcr-1 poses a significant public health threat, requiring global monitoring and surveillance. Here, we characterize the global distribution of mcr-1 using a data set of 457 mcr-1-positive sequenced isolates. We find mcr-1 in various plasmid types but identify an immediate background common to all mcr-1 sequences. Our analyses establish that all mcr-1 elements in circulation descend from the same initial mobilization of mcr-1 by an ISApl1 transposon in the mid 2000s (2002-2008; 95% highest posterior density), followed by a marked demographic expansion, which led to its current global distribution. Our results provide the first systematic phylogenetic analysis of the origin and spread of mcr-1, and emphasize the importance of understanding the movement of antibiotic resistance genes across multiple levels of genomic organization.