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Walker, A. S.

Publications and source records attributed to Walker, A. S..

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Identifying mixed Mycobacterium tuberculosis infection and laboratory cross-contamination during Mycobacterial sequencing programs

IntroductionDetecting laboratory cross-contamination and mixed tuberculosis infection are important goals of clinical Mycobacteriology laboratories.\n\nObjectivesTo develop a method detecting mixtures of different M. tuberculosis lineages in laboratories performing Mycobacterial next generation sequencing (NGS).\n\nSettingPublic Health England National Mycobacteriology Laboratory Birmingham, which performs Illumina sequencing on DNA extracted from positive Mycobacterial Growth Indicator tubes.\n\nMethodsWe analysed 4,156 samples yielding M. tuberculosis from 663 MiSeq runs, obtained during development and production use of a diagnostic process using NGS. Counts of the most common (major) variant, and all other variants (non-major variants) were determined from reads mapping to positions defining M. tuberculosis lineages. Expected variation was estimated during process development.\n\nResultsFor each sample we determined the non-major variant proportions at 55 sets of lineage defining positions. The non-major variant proportion in the two most mixed lineage defining sets (F2 metric) was compared with that in the 47 least mixed lineage defining sets (F47 metric). Three patterns were observed: (i) not mixed by either metric, (ii) high F47 metric suggesting mixtures of multiple lineages, and (iii) samples compatible with mixtures of two lineages, detected by differential F2 metric elevation relative to F47. Pattern (ii) was observed in batches, with similar patterns in the H37Rv control present in each run, and is likely to reflect cross-contamination. During production, the proportions of samples in each pattern were 97%, 2.8%, and 0.001%, respectively.\n\nConclusionThe F2 and F47 metrics described could be used for laboratory process control in laboratories sequencing M. tuberculosis.

microbiology

TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data

Much of the worldwide dissemination of antibiotic resistance has been driven by resistance gene associations with mobile genetic elements (MGEs), such as plasmids and transposons. Although increasing, our understanding of resistance spread remains relatively limited, as methods for tracking mobile resistance genes through multiple species, strains and plasmids are lacking. We have developed a bioinformatic pipeline for tracking variation within, and mobility of, specific transposable elements (TEs), such as transposons carrying antibiotic resistance genes. TETyper takes short-read whole-genome sequencing data as input and identifies single-nucleotide mutations and deletions within the TE of interest, to enable tracking of specific sequence variants, as well as the surrounding genetic context(s), to enable identification of transposition events. To investigate global dissemination of Klebsiella pneumoniae carbapenemase (KPC) and its associated transposon Tn4401, we applied TETyper to a collection of >3000 publicly available Illumina datasets containing blaKPC. This revealed surprising diversity, with >200 distinct flanking genetic contexts for Tn4401, indicating high levels of transposition. Integration of sample metadata revealed insights into associations between geographic locations, host species, Tn4401 sequence variants and flanking genetic contexts. To demonstrate the ability of TETyper to cope with high copy number TEs and to track specific short-term evolutionary changes, we also applied it to the insertion sequence IS26 within a defined K. pneumoniae outbreak. TETyper is implemented in python and is freely available at https://github.com/aesheppard/TETyper.

bioinformatics

A role for tetracycline selection in the evolution of Clostridium difficile PCR-ribotype 078

Farm animals have been identified as reservoirs of Clostridium difficile PCR-ribotype 078 (RT078). Since 2005, the incidence of human clinical cases (frequently severe), with this genotype has increased. We aimed to understand this change, by studying the recent evolutionary history of RT078. Phylogenetic analysis of international genomes (isolates from 2006-2014) revealed several recent clonal expansions. A common ancestor of each expansion had independently acquired different alleles of the tetracycline resistance gene tetM. Consequently, an unusually high proportion of RT078 genomes were tetM positive (76.5%). Additional tetracycline resistance determinants were also identified, some for the first time in C. difficile (efflux pump tet40). Each tetM-clonal expansion lacked geographic structure, indicating rapid international spread. Resistance determinants for C. difficile-infection-triggering antimicrobials including fluoroquinolones and clindamycin were comparatively rare in RT078. Tetracyclines are used intensively in agriculture; this selective pressure, plus rapid spread via the food-chain may explain the increased RT078 prevalence in humans.

microbiology

Control of artefactual variation in reported inter-sample relatedness during clinical use of a Mycobacterium tuberculosis sequencing pipeline

Contact tracing requires reliable identification of closely related bacterial isolates. When we noticed the reporting of artefactual variation between M. tuberculosis isolates during routine next generation sequencing of Mycobacterium spp, we investigated its basis in 2,018 consecutive M. tuberculosis isolates. In the routine process used, clinical samples were decontaminated and inoculated into broth cultures; from positive broth cultures DNA was extracted, sequenced, reads mapped, and consensus sequences determined. We investigated the process of consensus sequence determination, which selects the most common nucleotide at each position. Having determined the high-quality read depth and depth of minor variants across 8,006 M. tuberculosis genomic regions, we quantified the relationship between the minor variant depth and the amount of non-Mycobacterial bacterial DNA, which originates from commensal microbes killed during sample decontamination. In the presence of non-Mycobacterial bacterial DNA, we found significant increases in minor variant frequencies of more than 1.5 fold in 242 regions covering 5.1% of the M. tuberculosis genome. Included within these were four high variation regions strongly influenced by the amount of non-Mycobacterial bacterial DNA. Excluding these four regions from pairwise distance comparisons reduced biologically implausible variation from 5.2% to 0% in an independent validation set derived from 226 individuals. Thus, we have demonstrated an approach identifying critical genomic regions contributing to clinically relevant artefactual variation in bacterial similarity searches. The approach described monitors the outputs of the complex multi-step laboratory and bioinformatics process, allows periodic process adjustments, and will have application to quality control of routine bacterial genomics.

microbiology

A perturbation model of the gut microbiome’s response to antibiotics

Treatment with antibiotics is one of the most extreme perturbations to the human microbiome. Even standard courses of antibiotics dramatically reduce the microbiomes diversity and can cause transitions to dysbiotic states. Conceptually, this is often described as a stability landscape: the microbiome sits in a landscape with multiple stable equilibria, and sufficiently strong perturbations can shift the microbiome from its normal equilibrium to another state. However, this picture is only qualitative and has not been incorporated in previous mathematical models of the effects of antibiotics. Here, we outline a simple quantitative model based on the stability landscape concept and demonstrate its success on real data. Our analytical impulse-response model has minimal assumptions with three parameters. We fit this model in a Bayesian framework to previously published data on the year-long effects of four common antibiotics (ciprofloxacin, clindamycin, minocycline, and amoxicillin) on the gut and oral microbiomes, allowing us to compare parameters between antibiotics and microbiomes. Furthermore, using Bayesian model selection we find support for a long-term transition to an alternative microbiome state after courses of ciprofloxacin and clindamycin in both the gut and salivary microbiomes. Quantitative stability landscape frameworks are an exciting avenue for future microbiome modelling.

microbiology

Severe infections emerge from the microbiome by adaptive evolution

Bacteria responsible for the greatest global mortality colonize the human microbiome far more frequently than they cause severe infections. Whether mutation and selection within the microbiome accompany infection is unknown. We investigated de novo mutation in 1163 Staphylococcus aureus genomes from 105 infected patients with nose-colonization. We report that 72% of infections emerged from the microbiome, with infecting and nose-colonizing bacteria showing parallel adaptive differences. We found 2.8-to-3.6-fold enrichments of protein-altering variants in genes responding to rsp, which regulates surface antigens and toxicity; agr, which regulates quorum-sensing, toxicity and abscess formation; and host-derived antimicrobial peptides. Adaptive mutations in pathogenesis-associated genes were 3.1-fold enriched in infecting but not nose-colonizing bacteria. None of these signatures were observed in healthy carriers nor at the species-level, suggesting disease-associated, short-term, within-host selection pressures. Our results show that infection, like a cancer of the microbiome, emerges through spontaneous adaptive evolution, raising new possibilities for diagnosis and treatment.\n\nOne Sentence SummaryLife-threatening S. aureus infections emerge from nose microbiome bacteria in association with repeatable adaptive evolution.

genomics

Genomic epidemiology of global Klebsiella pneumoniae carbapenemase (KPC)-producing E. coli

The dissemination of carbapenem resistance in Escherichia coli has major implications for the management of common human infections. blaKPC, encoding a transmissible carbapenemase (KPC), has historically largely been associated with Klebsiella pneumoniae, a predominant plasmid (pKpQIL), and a specific transposable element (Tn4401, ~10kb). Here we characterize the genetic features of the emergence of blaKPC in global E. coli, 2008-2013, using both long-and short-read whole genome sequencing.\n\nAmongst 43/45 successfully sequenced blaKPC-E. coli strains, we identified high strain (n=21 sequence types, 18% of annotated genes in the core genome); plasmid ([≥]9 replicon types); and blaKPC-associated, mobile genetic element (MGE) diversity (50% not within complete Tn4401 elements). We also found evidence of interspecies, regional and international plasmid spread. In several cases blaKPC was found on high copy number, small Col-like plasmids, previously associated with horizontal transmission of resistance genes in the absence of antimicrobial selection pressures.\n\nE. coli is a common human pathogen, but also a commensal in a multiple environmental and animal reservoirs, and easily transmissible. The association of blaKPC with a range of MGEs previously linked to the successful spread of widely endemic resistance mechanisms (e.g. blaTEM, blaCTX-M) suggests that it is likely to become similarly prevalent.

microbiology

High rates of human faecal carriage of mcr-1-positive multi-drug resistant isolates emerge in China in association with successful plasmid families

SynopsisO_ST_ABSBackgroundC_ST_ABSmcr-1-mediated transmissible colistin resistance in Enterobacteriaceae is concerning, given colistin is frequently used as a treatment of last resort in multidrug-resistant Enterobacteriaceae infections. Reported rates of human mcr-1 gastrointestinal carriage have historically been low.\n\nObjectivesTo identify trends in human gastrointestinal carriage of mcr-1 positive and mcr-1-positive/cefotaxime-resistant Enterobacteriaceae in Guangzhou, China, 2011-2016, and investigate the genetic contexts of mcr-1 in a subset of mcr-1-positive/cefotaxime-resistant strains using whole genome sequencing (WGS).\n\nMethodsOf 8,022 faecal samples collected, 497 (6.2%) were mcr-1- positive, and 182 (2.3%) mcr-1-positive/cefotaxime-resistant. Trends in carriage were assessed using iterative sequential regression. A subset of mcr-1-positive isolates was sequenced (Illumina), and genetic contexts of mcr-1 were characterised.\n\nResultsWe observed marked increases in mcr-1 (now ~30% prevalence) and more recent (since January 2014) increases in mcr-1-positive/third-generation cephalosporin-resistant Enterobacteriaceae human colonisation (p<0.001). Sub-cultured mcr-1-positive/third-generation cephalosporin-resistant isolates were commonly multi-drug resistant.\n\nWGS of 50 mcr-1/third-generation cephalosporin-resistant isolates (49 Escherichia coli; 1 Klebsiella pneumoniae) demonstrated bacterial strain diversity (39 E. coli sequence types); mcr-1 in association with common plasmid backbones (IncI, IncHI2/HI2A, IncX4) and sometimes in multiple plasmids; frequent mcr-1 chromosomal integration; and loss of the mcr-1-associated insertion sequence ISApl1 in some plasmids. Significant sequence similarity with published mcr-1 plasmid sequences was consistent with spread amongst pig, chicken and human reservoirs.\n\nConclusionsThe high positivity rate (~10%) of mcr-1 in multidrug-resistant E. coli colonising humans is a clinical threat; the diverse genetic mechanisms (strains/plasmids/insertion sequences) associated with mcr-1 have likely contributed to its dissemination, and will facilitate its persistence.

microbiology

Same-day diagnostic and surveillance data for tuberculosis via whole genome sequencing of direct respiratory samples.

Routine full characterization of Mycobacterium tuberculosis (TB) is culture-based, taking many weeks. Whole-genome sequencing (WGS) can generate antibiotic susceptibility profiles to inform treatment, augmented with strain information for global surveillance; such data could be transformative if provided at or near point of care.\n\nWe demonstrate a low-cost DNA extraction method for TB WGS direct from patient samples. We initially evaluated the method using the Illumina MiSeq sequencer (40 smear-positive respiratory samples, obtained after routine clinical testing, and 27 matched liquid cultures). M. tuberculosis was identified in all 39 samples from which DNA was successfully extracted. Sufficient data for antibiotic susceptibility prediction was obtained from 24 (62%) samples; all results were concordant with reference laboratory phenotypes. Phylogenetic placement was concordant between direct and cultured samples. Using an Illumina MiSeq/MiniSeq the workflow from patient sample to results can be completed in 44/16 hours at a cost of {pound}96/{pound}198 per sample.\n\nWe then employed a non-specific PCR-based library preparation method for sequencing on an Oxford Nanopore Technologies MinION sequencer. We applied this to cultured Mycobacterium bovis BCG strain (BCG), and to combined culture-negative sputum DNA and BCG DNA. For the latest flowcell, the estimated turnaround time from patient to identification of BCG was 6 hours, with full susceptibility and surveillance results 2 hours later. Antibiotic susceptibility predictions were fully concordant. A critical advantage of the MinION is the ability to continue sequencing until sufficient coverage is obtained, providing a potential solution to the problem of variable amounts of M. tuberculosis in direct samples.

microbiology