ORCID Profile
0000-0001-8466-7547
Current Organisations
EMBL-EBI
,
University of Oxford
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Massachusetts Medical Society
Date: 11-10-2018
Publisher: Springer Science and Business Media LLC
Date: 31-10-2012
DOI: 10.1038/NATURE11632
Publisher: Cold Spring Harbor Laboratory
Date: 11-12-2020
DOI: 10.1101/2020.12.09.20246397
Abstract: Vietnam has high rates of antimicrobial resistance (AMR) but limited capacity for genomic surveillance. This study used whole genome sequencing (WGS) to examine the prevalence and transmission of three key AMR pathogens in two intensive care units in Hanoi, Vietnam. A prospective surveillance study of all adults admitted to intensive care units (ICUs) at the National Hospital for Tropical Diseases (NHTD) and Bach Mai Hospital (BMH) was conducted between June 2017 and January 2018. Clinical and environmental s les were cultured on selective media, characterised using MALDI TOF MS, and illumina sequenced. Phylogenies based on the de novo assemblies (SPAdes) were constructed using Mafft (PARsnp), Gubbins and RAxML. Resistance genes were detected using Abricate against the NCBI database. 3,153 Escherichia coli, Klebsiella pneumoniae and Acinetobacter baumannii isolates from 369 patients were analysed. Phylogenetic analysis revealed predominant lineages within A. baumannii (global clone [GC]2, sequence types [ST]2, ST571) and K. pneumoniae (ST15, ST16, ST656, ST11, ST147) isolates. Colonisation was most common with E. coli (88.9%) followed by K. pneumoniae (62.4%). Of the E. coli , 91% carried a bla CTX-M variant, while 81% of K. pneumoniae isolates carried bla NDM (54%) and/or bla KPC (45%). Transmission analysis using single nucleotide polymorphisms (SNPs) identified 167 clusters involving 251 (68%) patients, in some cases involving patients from both ICUs. There were no significant differences between the lineages or AMR genes recovered between the two ICUs. This study represents the largest prospective surveillance study of key AMR pathogens in Vietnamese ICUs. Clusters of closely related isolates in patients across both ICUs suggests recent transmission prior to ICU admission in other healthcare settings or in the community. This work was funded by the Medical Research Council Newton Fund, United Kingdom the Ministry of Science and Technology, Vietnam and the Wellcome Trust, United Kingdom. Globally, antimicrobial resistance (AMR) is projected to cause 10 million deaths annually by 2050. Ninety percent of these deaths are expected to occur in low- and middle-income countries (LMICs), but attributing morbidity and mortality to AMR is difficult in the absence of comprehensive data. Whilst efforts have been made to improve AMR surveillance in these settings, this is often h ered by limited expertise, laboratory infrastructure and financial resources. This is the largest prospective surveillance study of three key AMR pathogens ( E. coli, K. pneumoniae and A. baumannii ) conducted in critical care settings in Vietnam. S ling was restricted to patients who were colonised or infected with extended spectrum beta-lactamase (ESBL) producing and/or carbapenem-resistant organisms. Colonisation with more than one organism was very common, with multidrug-resistant (MDR) E. coli being predominant in stool s les. A small number of predominant lineages were identified for K. pneumoniae and A. baumannii , while the E. coli isolates were highly genetically erse. A large number of genomic clusters were identified within the two ICUs, some of which spanned both ICUs. There were no significant differences between lineages or AMR genes between the two ICUs. This study found high rates of colonisation and infection with three key AMR pathogens in adults admitted to two Vietnamese ICUs. Whilst transmission was common within ICUs the finding of similar lineages and AMR genes in both ICUs suggests that dissemination of AMR occurs prior to ICU admission, either in referral hospitals or in community settings prior to hospital admission. Strategies to tackle AMR in Vietnam will need to account for this by extending surveillance more widely across hospital and community settings.
Publisher: Microbiology Society
Date: 08-08-2023
Abstract: Tuberculosis is a global pandemic disease with a rising burden of antimicrobial resistance. As a result, the World Health Organization (WHO) has a goal of enabling universal access to drug susceptibility testing (DST). Given the slowness of and infrastructure requirements for phenotypic DST, whole-genome sequencing, followed by genotype-based prediction of DST, now provides a route to achieving this. Since a central component of genotypic DST is to detect the presence of any known resistance-causing mutations, a natural approach is to use a reference graph that allows encoding of known variation. We have developed DrPRG (Drug resistance Prediction with Reference Graphs) using the bacterial reference graph method Pandora. First, we outline the construction of a Mycobacterium tuberculosis drug resistance reference graph. The graph is built from a global dataset of isolates with varying drug susceptibility profiles, thus capturing common and rare resistance- and susceptible-associated haplotypes. We benchmark DrPRG against the existing graph-based tool Mykrobe and the haplotype-based approach of TBProfiler using 44 709 and 138 publicly available Illumina and Nanopore s les with associated phenotypes. We find that DrPRG has significantly improved sensitivity and specificity for some drugs compared to these tools, with no significant decreases. It uses significantly less computational memory than both tools, and provides significantly faster runtimes, except when runtime is compared to Mykrobe with Nanopore data. We discover and discuss novel insights into resistance-conferring variation for M. tuberculosis – including deletion of genes katG and pncA – and suggest mutations that may warrant reclassification as associated with resistance.
Publisher: Microbiology Society
Date: 03-2018
DOI: 10.1099/JMM.0.000664
Publisher: Springer Science and Business Media LLC
Date: 11-12-1994
DOI: 10.1038/NATURE15393
Publisher: Cold Spring Harbor Laboratory
Date: 04-05-2023
DOI: 10.1101/2023.05.04.539481
Abstract: 2. The dominant paradigm for analysing genetic variation relies on a central idea: all genomes in a species can be described as minor differences from a single reference genome. However, this approach can be problematic or inadequate for bacteria, where there can be significant sequence ergence within a species. Reference graphs are an emerging solution to the reference bias issues implicit in the “single-reference” model. Such a graph represents variation at multiple scales within a population – e.g., nucleotide- and locus-level. The genetic causes of drug resistance in bacteria have proven comparatively easy to decode compared with studies of human diseases. For ex le, it is possible to predict resistance to numerous anti-tuberculosis drugs by simply testing for the presence of a list of single nucleotide polymorphisms and insertion/deletions, commonly referred to as a catalogue. We developed DrPRG (Drug resistance Prediction with Reference Graphs) using the bacterial reference graph method Pandora. First, we outline the construction of a Mycobacterium tuberculosis drug resistance reference graph, a process that can be replicated for other species. The graph is built from a global dataset of isolates with varying drug susceptibility profiles, thus capturing common and rare resistance- and susceptible-associated haplotypes. We benchmark DrPRG against the existing graph-based tool Mykrobe and the haplotype-based approach of TBProfiler using 44,709 and 138 publicly available Illumina and Nanopore s les with associated phenotypes. We find DrPRG has significantly improved sensitivity and specificity for some drugs compared to these tools, with no significant decreases. It uses significantly less computational memory than both tools, and provides significantly faster runtimes, except when runtime is compared to Mykrobe on Nanopore data. We discover and discuss novel insights into resistance-conferring variation for M. tuberculosis - including deletion of genes katG and pncA – and suggest mutations that may warrant reclassification as associated with resistance. 3. Mycobacterium tuberculosis is the bacterium responsible for tuberculosis (TB). TB is one of the leading causes of death worldwide before the coronavirus pandemic it was the leading cause of death from a single pathogen. Drug-resistant TB incidence has recently increased, making the detection of resistance even more vital. In this study, we develop a new software tool to predict drug resistance from whole-genome sequence data of the pathogen using new reference graph models to represent a reference genome. We evaluate it on M. tuberculosis against existing tools for resistance prediction and show improved performance. Using our method, we discover new resistance-associated variations and discuss reclassification of a selection of existing mutations. As such, this work contributes to TB drug resistance diagnostic efforts. In addition, the method could be applied to any bacterial species, so is of interest to anyone working on antimicrobial resistance. 4. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files . The software method presented in this work, DrPRG, is freely available from GitHub under an MIT license at bhall88/drprg . We used commit 9492f25 for all results via a Singularity[1] container from the URI docker://quay.io/mbhall88/drprg:9492f25 . All code used to generate results for this study are available on GitHub at bhall88/drprg-paper . All data used in this work are freely available from the SRA/ENA/DRA and a copy of the datasheet with all associated phenotype information can be downloaded from the archived repository at 0.5281/zenodo.7819984 or found in the previously mentioned GitHub repository. The Mycobacterium tuberculosis index used in this work is available to download through DrPRG via the command drprg index --download mtb@20230308 or from GitHub at bhall88/drprg-index .
Publisher: eLife Sciences Publications, Ltd
Date: 19-12-2017
DOI: 10.7554/ELIFE.30637
Abstract: Bacteria responsible for the greatest global mortality colonize the human microbiota far more frequently than they cause severe infections. Whether mutation and selection among commensal bacteria are associated with 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 nose, with infecting and nose-colonizing bacteria showing parallel adaptive differences. We found 2.8-to-3.6-fold adaptive enrichments of protein-altering variants in genes responding to rsp, which regulates surface antigens and toxin production agr, which regulates quorum-sensing, toxin production 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 infection-associated, short-term, within-host selection pressures. Our results show that signatures of spontaneous adaptive evolution are specifically associated with infection, raising new possibilities for diagnosis and treatment.
Publisher: Springer Science and Business Media LLC
Date: 21-12-2015
DOI: 10.1038/NCOMMS10063
Abstract: The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical s les, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial ersity 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.
Publisher: American Society for Microbiology
Date: 09-2018
DOI: 10.1128/JCM.01815-17
Abstract: In principle, whole-genome sequencing (WGS) can predict phenotypic resistance directly from a genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date.
Publisher: Cold Spring Harbor Laboratory
Date: 29-10-2020
DOI: 10.1101/2020.10.29.360040
Abstract: Shigella sonnei is the most common agent of shigellosis in high-income countries, and causes a significant disease burden in low- and middle-income countries. Antimicrobial resistance is increasingly common in all settings. Whole genome sequencing (WGS) is increasingly utilised for S. sonnei outbreak investigation and surveillance, but comparison of data between studies and labs is challenging. Here, we present a genomic framework and genotyping scheme for S. sonnei to efficiently identify genotype and resistance determinants from WGS data. The scheme is implemented in the software package Mykrobe and tested on thousands of genomes. Applying this approach to analyse ,000 S. sonnei isolates sequenced in public health labs in three countries identified several common genotypes associated with increased rates of ciprofloxacin resistance and azithromycin resistance, confirming intercontinental spread of highly-resistant S. sonnei clones and demonstrating the genomic framework can facilitate monitoring of the emergence and spread of resistant clones at local and global scales.
Publisher: Cold Spring Harbor Laboratory
Date: 14-03-2017
DOI: 10.1101/116681
Abstract: 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. Life-threatening S. aureus infections emerge from nose microbiome bacteria in association with repeatable adaptive evolution.
Publisher: Springer Science and Business Media LLC
Date: 09-02-2015
DOI: 10.1038/NG.3215
Publisher: Springer Science and Business Media LLC
Date: 11-05-2021
DOI: 10.1038/S41467-021-22700-4
Abstract: Shigella sonnei is the most common agent of shigellosis in high-income countries, and causes a significant disease burden in low- and middle-income countries. Antimicrobial resistance is increasingly common in all settings. Whole genome sequencing (WGS) is increasingly utilised for S. sonnei outbreak investigation and surveillance, but comparison of data between studies and labs is challenging. Here, we present a genomic framework and genotyping scheme for S. sonnei to efficiently identify genotype and resistance determinants from WGS data. The scheme is implemented in the software package Mykrobe and tested on thousands of genomes. Applying this approach to analyse ,000 S. sonnei isolates sequenced in public health labs in three countries identified several common genotypes associated with increased rates of ciprofloxacin resistance and azithromycin resistance, confirming intercontinental spread of highly-resistant S. sonnei clones and demonstrating the genomic framework can facilitate monitoring the spread of resistant clones, including those that have recently emerged, at local and global scales.
Publisher: Springer Science and Business Media LLC
Date: 14-09-2021
DOI: 10.1186/S13059-021-02473-1
Abstract: We present pandora , a novel pan-genome graph structure and algorithms for identifying variants across the full bacterial pan-genome. As much bacterial adaptability hinges on the accessory genome, methods which analyze SNPs in just the core genome have unsatisfactory limitations. Pandora approximates a sequenced genome as a recombinant of references, detects novel variation and pan-genotypes multiple s les. Using a reference graph of 578 Escherichia coli genomes, we compare 20 erse isolates. Pandora recovers more rare SNPs than single-reference-based tools, is significantly better than picking the closest RefSeq reference, and provides a stable framework for analyzing erse s les without reference bias.
Publisher: Cold Spring Harbor Laboratory
Date: 16-09-2021
DOI: 10.1101/2021.09.14.458035
Abstract: There remains a clinical need for better approaches to rapid drug susceptibility testing in view of the increasing burden of multidrug resistant tuberculosis. Binary susceptibility phenotypes only capture changes in minimum inhibitory concentration when these cross the critical concentration, even though other changes may be clinically relevant. We developed a machine learning system to predict minimum inhibitory concentration from unassembled whole-genome sequencing data for 13 anti-tuberculosis drugs. We trained, validated and tested the system on 10,859 isolates from the CRyPTIC dataset. Essential agreement rates (predicted MIC within one doubling dilution of observed MIC) were above 92% for first-line drugs, 91% for fluoroquinolones and aminoglycosides, and 90% for new and repurposed drugs, albeit with a significant drop in performance for the very few phenotypically resistant isolates in the latter group. To further validate the model in the absence of external MIC datasets, we predicted MIC and converted values to binary for an external set of 15,239 isolates with binary phenotypes, and compare their performance against a previously validated mutation catalogue, the expected performance of existing molecular assays, and World Health Organization Target Product Profiles. The sensitivity of the model on the external dataset was greater than 90% for all drugs except ethionamide, clofazimine and linezolid. Specificity was greater than 95% for all drugs except ethambutol, ethionamide, bedaquiline, delamanid and clofazimine. The proposed system can provide quantitative susceptibility phenotyping to help guide antimicrobial therapy, although further data collection and validation are required before machine learning can be used clinically for all drugs.
Publisher: Cold Spring Harbor Laboratory
Date: 15-09-2021
DOI: 10.1101/2021.09.15.460475
Abstract: Short-read variant calling for bacterial genomics is a mature field, and there are many widely-used software tools. Different underlying approaches (eg pileup, local or global assembly, paired-read use, haplotype use) lend each tool different strengths, especially when considering non-SNP (single nucleotide polymorphism) variation or potentially distant reference genomes. It would therefore be valuable to be able to integrate the results from multiple variant callers, using a robust statistical approach to “adjudicate” at loci where there is disagreement between callers. To this end, we present a tool, Minos, for variant adjudication by mapping reads to a genome graph of variant calls. Minos allows users to combine output from multiple variant callers without loss of precision. Minos also addresses a second problem of joint genotyping SNPs and indels in bacterial cohorts, which can also be framed as an adjudication problem. We benchmark on 62 s les from 3 species ( Mycobacterium tuberculosis, Staphylococcus aureus, Klebsiella pneumoniae ) and an outbreak of 385 M. tuberculosis s les. Finally, we joint genotype a large M. tuberculosis cohort (N ≈ 15k) for which the rif icin phenotype is known. We build a map of non-synonymous variants in the RRDR (rif icin resistance determining region) of the rpoB gene and extend current knowledge relating RRDR SNPs to heterogeneity in rif icin resistance levels. We replicate this finding in a second M. tuberculosis cohort (N ≈ 13k). Minos is released under the MIT license, available at qbal-lab-org/minos .
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 02-2023
Publisher: Proceedings of the National Academy of Sciences
Date: 20-11-2013
Abstract: Harvey rat sarcoma viral oncogene homolog ( HRAS ) occupies an important place in medical history, because it was the first gene in which acquired mutations that led to activation of a normal protein were associated with cancer, making it the prototype of the now canonical oncogene mechanism. Here, we explore what happens when similar HRAS mutations occur in male germ cells, an issue of practical importance because the mutations cause a serious congenital disorder, Costello syndrome, if transmitted to offspring. We provide evidence that the mutant germ cells are positively selected, leading to an increased burden of the mutations as men age. Although there are many parallels between this germline process and classical oncogenesis, there are interesting differences of detail, which are explored in this paper.
Publisher: Cold Spring Harbor Laboratory
Date: 08-03-2022
DOI: 10.1101/2022.03.04.22271870
Abstract: Mycobacterium tuberculosis whole-genome sequencing (WGS) using Illumina technology has been widely adopted for genotypic drug susceptibility testing (DST) and outbreak investigation. Oxford Nanopore Technologies is reported to have higher error rates but has not been thoroughly evaluated for these applications. We analyse 151 isolates from Madagascar, South Africa and England with phenotypic DST and matched Illumina and Nanopore data. Using PacBio assemblies, we select Nanopore filters for BCFtools (software) detection of single nucleotide polymorphisms (SNPs). We compare transmission clusters identified by Nanopore and the United Kingdom Health Security Agency Illumina pipeline (COMPASS). We compare Illumina and Nanopore WGS-based DST predictions using Mykrobe (software). Nanopore/BCFtools identifies SNPs with median precision/recall of 99·5/90·2% compared with 99·6/91·9% for Illumina/COMPASS. Using a threshold of 12 SNPs for putative transmission clusters, Illumina identifies 98 isolates as unrelated and 53 as belonging to 19 distinct clusters (size range 2-7). Nanopore reproduces this distribution with addition of 5 singleton isolates to distinct clusters and merging of two cluster pairs. Illumina-based clusters are also replicated using a 5 SNP threshold. Clustering accuracy is maintained using mixed Illumina/Nanopore datasets. Genotyping resistance variants is highly concordant, with 0(4) discordant SNPs (indels) across 151 isolates genotyped at (60,000) SNPs (indels). Illumina and Nanopore sequence data provide comparable cluster-identification and DST results. Academy for Medical Sciences (SGL018\\110), Oxford Wellcome Institutional Strategic Support Fund (ISSF TT17 4). Swiss South Africa Joint Research Award (Swiss national science Foundation and South African national research foundation). Two key types of information can be obtained from laboratory testing of M. tuberculosis isolates to help directly guide public health interventions: drug susceptibility testing (DST) to guide therapy, and bacterial typing to enrich understanding of the epidemiology and guide interventions to mitigate transmission. DST is typically performed by the “gold standard” culture-based phenotyping method or nucleic acid lification assays targeting specific resistance-conferring mutations. Studies over the last 7 years have shown that prediction of susceptibility profile using Illumina-technology genome sequence data is possible, and can be automated. In a key publication, the CRyPTIC consortium and UK 100,000 Genomes project evaluated the method on over 10,000 genomes including prospectively s led isolates and showed that for first-line tuberculosis (TB) drugs (isoniazid, rif icin, ethambutol, pyrazinamide) a pan-susceptibility profile is accurate enough to be used clinically. The genetic basis of resistance remains imperfectly understood for second-line TB drugs, in particular for new and repurposed drugs (bedaquiline, clofazimine, delamanid, linezolid). Prior work in the field of genotypic DST was heavily based on Illumina technology, which provides short (70-300 base pair) sequence reads of very high quality. Many different softwares (e.g. TBProfiler, Mykrobe, MTBseq, kvarq) have been designed for sequence analysis and genotypic DST. However, the increasingly used Nanopore sequencing platforms yield very different data with much longer sequence reads (frequently over 1kb) and higher error rates including systematic biases. To date, very limited evaluation of Nanopore-based drug susceptibility prediction has been performed using the only two compatible tools (Mykrobe (n=5 independent s les), TBProfiler (n=3 independent s les)). Molecular typing of M. tuberculosis allows lineage identification and detection of putative transmission clusters. In the last decade, multiple M. tuberculosis molecular epidemiology studies have shown how genomic information can complement traditional epidemiology in identifying person-to-person transmission clusters with a high level of resolution. Typically, the number of single nucleotide polymorphism (SNP) disagreements between genomes, or SNP distance, is calculated and single-linkage clustering is performed for genomes falling within retrospectively established transmission thresholds of either 5 or 12 SNPs. Just as with DST, these thresholds were established with Illumina sequencing data. The increased error rate in Nanopore sequencing is believed to lead to inflated SNP distances if standard genome analysis tools are used. Prior to this study it was unknown what impact on isolate-clustering this would incur. Full-scale adoption of genomic sequencing in tuberculosis reference laboratories has so far taken place in a limited number of settings - England, the Netherlands, and New York State - all using Illumina-based sequencing data. Building on current evidence, specific WHO technical guidance and ersification and democratisation of technology, sequencing is expected to be increasingly used in tuberculosis control globally. For the first time, our study offers 4 key deliverables intended to inform adoption of Nanopore technology as an alternative, or a complement, to Illumina. First: a systematic head-to-head comparison of Nanopore and Illumina data for M. tuberculosis drug susceptibility profiling and isolate clustering, including quantitative metrics for cluster precision and recall. Second: an assessment of the impact of mixed Illumina and Nanopore data on clustering which represents an increasingly common challenge. Third: an open-source software pipeline allowing research and reference laboratories to replicate our analytical approach. Fourth: a publicly available curated test set of 151 isolates, including matched Illumina and Nanopore sequence data, and (for a subset of seven isolates) high-quality PacBio assemblies, for method development and validation. Catalogues of drug resistance conferring mutations will keep improving, especially for new and repurposed drugs. Our data confirms that Illumina and Nanopore sequencing technologies can be used to identify those mutations equally accurately in M. tuberculosis . Bacterial molecular typing is constantly shown to support the understanding of disease transmission and tuberculosis control in new settings. The bioinformatics tools and filters we have developed, assessed, and made publicly available allow the use of Nanopore or mixed-technology data to appropriately cluster genetically related isolates. We provide a measure of the expected level of over-clustering associated with Nanopore technology. This study confirms that Illumina and Nanopore sequence data provide comparable DST results and isolate cluster-identification.
Publisher: Cold Spring Harbor Laboratory
Date: 12-11-2020
DOI: 10.1101/2020.11.12.380378
Abstract: Bacterial genomes follow a U-shaped frequency distribution whereby most genomic loci are either rare (accessory) or common (core) the union of these is the pan-genome. The alignable fraction of two genomes from a single species can be low (e.g. 50-70%), such that no single reference genome can access all single nucleotide polymorphisms (SNPs). The pragmatic solution is to choose a close reference, and analyse SNPs only in the core genome. Given much bacterial adaptability hinges on the accessory genome, this is an unsatisfactory limitation. We present a novel pan-genome graph structure and algorithms implemented in the software pandora , which approximates a sequenced genome as a recombinant of reference genomes, detects novel variation and then pan-genotypes multiple s les. The method takes fastq as input and outputs a multi-s le VCF with respect to an inferred data-dependent reference genome, and is available at mcolq andora . Constructing a reference graph from 578 E. coli genomes, we analyse a erse set of 20 E. coli isolates. We show pandora recovers at least 13k more rare SNPs than single-reference based tools, achieves equal or better error rates with Nanopore as with Illumina data, 6-24x lower Nanopore error rates than other tools, and provides a stable framework for analysing erse s les without reference bias. We also show that our inferred recombinant VCF reference genome is significantly better than simply picking the closest RefSeq reference. This is a step towards comprehensive cohort analysis of bacterial pan-genomic variation, with potential impacts on genotype henotype and epidemiological studies.
Publisher: Cold Spring Harbor Laboratory
Date: 31-10-2022
DOI: 10.1101/2022.10.31.514503
Abstract: Universal access to drug susceptibility testing for newly diagnosed tuberculosis patients is recommended. Access to culture-based diagnostics remains limited and targeted molecular assays are vulnerable to emerging resistance conferring mutations. Improved s le preparation protocols for direct-from-sputum sequencing of Mycobacterium tuberculosis would accelerate access to comprehensive drug susceptibility testing and molecular typing. We assessed a thermo-protection buffer-based direct-from-s le M. tuberculosis whole-genome sequencing protocol. We prospectively processed and analyzed 60 acid-fast bacilli smear-positive sputum s les from tuberculosis patients in India and Madagascar. A ersity of semi-quantitative smear positivity level s les were included. Sequencing was performed using Illumina and MinION (monoplex and multiplex) technologies. We measured the impact of bacterial inoculum and sequencing platforms on M. tuberculosis genomic mean read depth, drug susceptibility prediction performance and typing accuracy. M. tuberculosis was identified from 88% (Illumina), 89% (MinION-monoplex) and 83% (MinION-multiplex) of s les for which sufficient DNA could be extracted. The fraction of M. tuberculosis reads from MinION sequencing was lower than from Illumina, but monoplexing grade 3+ sputum s les on MinION produced higher read depth than Illumina ( p .05) and MinION multiplex ( p .01). No significant difference in overall sensitivity and specificity of drug susceptibility predictions was seen across these sequencing modalities or within each sequencing technology when stratified by smear grade. Lineage typing agreement percentages between direct and culture-based sequencing were 85% (MinION-monoplex), 88% (Illumina) and 100% (MinION-multiplex) M. tuberculosis direct-from-s le whole-genome sequencing remains challenging. Improved and affordable s le treatment protocols are needed prior to clinical deployment.
Publisher: Centers for Disease Control and Prevention (CDC)
Date: 03-2021
Publisher: Proceedings of the National Academy of Sciences
Date: 05-03-2002
Abstract: Whole-genome sequencing offers new insights into the evolution of bacterial pathogens and the etiology of bacterial disease. Staphylococcus aureus is a major cause of bacteria-associated mortality and invasive disease and is carried asymptomatically by 27% of adults. Eighty percent of bacteremias match the carried strain. However, the role of evolutionary change in the pathogen during the progression from carriage to disease is incompletely understood. Here we use high-throughput genome sequencing to discover the genetic changes that accompany the transition from nasal carriage to fatal bloodstream infection in an in idual colonized with methicillin-sensitive S. aureus . We found a single, cohesive population exhibiting a repertoire of 30 single-nucleotide polymorphisms and four insertion/deletion variants. Mutations accumulated at a steady rate over a 13-mo period, except for a cluster of mutations preceding the transition to disease. Although bloodstream bacteria differed by just eight mutations from the original nasally carried bacteria, half of those mutations caused truncation of proteins, including a premature stop codon in an AraC -family transcriptional regulator that has been implicated in pathogenicity. Comparison with evolution in two asymptomatic carriers supported the conclusion that clusters of protein-truncating mutations are highly unusual. Our results demonstrate that bacterial ersity in vivo is limited but nonetheless detectable by whole-genome sequencing, enabling the study of evolutionary dynamics within the host. Regulatory or structural changes that occur during carriage may be functionally important for pathogenesis therefore identifying those changes is a crucial step in understanding the biological causes of invasive bacterial disease.
Publisher: Springer Science and Business Media LLC
Date: 20-04-2016
DOI: 10.1038/NCOMMS11465
Abstract: Nature Communications 6: Article number: 10063 (2015) Published: 21 December 2015 Updated: 20 April 2016 In Supplementary Data 3 of this Article, one of the Staphylococcus aureus accession codes is incorrect, as follows: SRR2101499 should be ERR1197981.
Publisher: Elsevier BV
Date: 11-2022
Publisher: Cold Spring Harbor Laboratory
Date: 26-04-2015
DOI: 10.1101/018564
Abstract: Rapid and accurate detection of antibiotic resistance in pathogens is an urgent need, affecting both patient care and population-scale control. Microbial genome sequencing promises much, but many barriers exist to its routine deployment. Here, we address these challenges, using a de Bruijn graph comparison of clinical isolate and curated knowledge-base to identify species and predict resistance profile, including minor populations. This is implemented in a package, Mykrobe predictor, for S. aureus and M. tuberculosis, running in under three minutes on a laptop from raw data. For S. aureus, we train and validate in 495/471 s les respectively, finding error rates comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.3%/99.5% across 12 drugs. For M. tuberculosis, we identify species and predict resistance with specificity of 98.5% (training/validating on 1920/1609 s les). Sensitivity of 82.6% is limited by current understanding of genetic mechanisms. We also show that analysis of minor populations increases power to detect phenotypic resistance in second-line drugs without appreciable loss of specificity. Finally, we demonstrate feasibility of an emerging single-molecule sequencing technique.
Publisher: Springer Science and Business Media LLC
Date: 05-07-2022
DOI: 10.1186/S13059-022-02714-X
Abstract: There are many short-read variant-calling tools, with different strengths and weaknesses. We present a tool, Minos, which combines outputs from arbitrary variant callers, increasing recall without loss of precision. We benchmark on 62 s les from three bacterial species and an outbreak of 385 Mycobacterium tuberculosis s les. Minos also enables joint genotyping we demonstrate on a large ( N =13 k ) M. tuberculosis cohort, building a map of non-synonymous SNPs and indels in a region where all such variants are assumed to cause rif icin resistance. We quantify the correlation with phenotypic resistance and then replicate in a second cohort ( N =10 k ).
Publisher: Elsevier BV
Date: 07-2016
Publisher: F1000 Research Ltd
Date: 02-12-2019
DOI: 10.12688/WELLCOMEOPENRES.15603.1
Abstract: Two billion people are infected with Mycobacterium tuberculosis , leading to 10 million new cases of active tuberculosis and 1.5 million deaths annually. Universal access to drug susceptibility testing (DST) has become a World Health Organization priority. We previously developed a software tool, Mykrobe predictor , which provided offline species identification and drug resistance predictions for M. tuberculosis from whole genome sequencing (WGS) data. Performance was insufficient to support the use of WGS as an alternative to conventional phenotype-based DST, due to mutation catalogue limitations. Here we present a new tool, Mykrobe , which provides the same functionality based on a new software implementation. Improvements include i) an updated mutation catalogue giving greater sensitivity to detect pyrazinamide resistance, ii) support for user-defined resistance catalogues, iii) improved identification of non-tuberculous mycobacterial species, and iv) an updated statistical model for Oxford Nanopore Technologies sequencing data. Mykrobe is released under MIT license at ykrobe-tools/mykrobe. We incorporate mutation catalogues from the CRyPTIC consortium et al. (2018) and from Walker et al. (2015), and make improvements based on performance on an initial set of 3206 and an independent set of 5845 M. tuberculosis Illumina sequences. To give estimates of error rates, we use a prospectively collected dataset of 4362 M. tuberculosis isolates . Using culture based DST as the reference, we estimate Mykrobe to be 100%, 95%, 82%, 99% sensitive and 99%, 100%, 99%, 99% specific for rif icin, isoniazid, pyrazinamide and ethambutol resistance prediction respectively. We benchmark against four other tools on 10207 (=5845+4362) s les, and also show that Mykrobe gives concordant results with nanopore data. We measure the ability of Mykrobe -based DST to guide personalized therapeutic regimen design in the context of complex drug susceptibility profiles, showing 94% concordance of implied regimen with that driven by phenotypic DST, higher than all other benchmarked tools.
Publisher: Cold Spring Harbor Laboratory
Date: 08-12-2022
DOI: 10.1101/2022.12.08.519610
Abstract: The antibiotic Bedaquiline (BDQ) is a key component of new WHO regimens for drug resistant tuberculosis (TB) but predicting BDQ resistance (BDQ-R) from genotypes remains challenging. We analysed a collection (n=505) of Mycobacterium tuberculosis from two high prevalence areas in South Africa (Cape Town and Johannesburg, 2019-2020), and found 53 independent acquisitions of 31 different mutations within the mmpR5 regulatory gene, with a particular enrichment of truncated MmpR5 in BDQ-R isolates by either frameshift or introduction of an insertion element. Truncations occurred across three M. tuberculosis lineages, impacting 66% of BDQ-R isolates. Extending our analysis to 1,961 isolates with minimum inhibitory concentrations (MICs) revealed that mmpR5 -disrupted isolates had a median BDQ MIC of 0.25 mg/L, compared to the wild-type median of 0.06 mg/L. By matching mmpR5 -disrupted isolates with phylogenetically close control isolates without the disruption, we were able to estimate the impact on MIC of in idual mutations. In conclusion, as the MIC increase borders the ECOFF threshold for BDQ-R, we recommend the continued use of MICs and detection of MmpR5 truncations to identify modest shifts in BDQ-R.
Publisher: American Society for Microbiology
Date: 23-03-2023
DOI: 10.1128/JCM.01578-22
Abstract: Universal access to drug susceptibility testing for newly diagnosed tuberculosis patients is recommended. Access to culture-based diagnostics remains limited, and targeted molecular assays are vulnerable to emerging resistance mutations.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Zamin Iqbal.