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Crook, D. W.

Publications and source records attributed to Crook, D. W..

At least 19 recordsLinked to original sources
bioRxiv2026

Long-read sequencing of Mycobacterial tuberculosis is comparable to short-read sequencing for antimicrobial resistance prediction and epidemiological studies.

BackgroundShort-read genetic sequencing technologies (mainly Illumina) have been extensively used for around a decade for Mycobacterium tuberculosis complex (MTBC) outbreak analysis and genomic drug susceptibility testing (gDST) with the result that Illumina has become the de facto gold standard. Long-read sequencing, as exemplified by Oxford Nanopore Technologies (ONT), offer the prospect of faster, simpler, and portable sequencing. In this work, we carry out the largest to date comparison of how well Illumina and ONT technologies sequence MTBC samples, making use of R10.4 ONT flowcells, updated basecalling models and deep-learning variant calling. MethodsA total of 508 samples were sequenced using both short and long-read platforms. All samples originated from South Africa or Vietnam and were over-selected for drug resistance and also included several local outbreaks and a range of lineages. The South African and Vietnamese samples had already been Illumina sequenced. Samples with [≥]50 read depth by Illumina were selected for sequencing by ONT using one of the GridION or PromethION platforms. Bioinformatics processing was done using a modified online cloud platform which included reference-based variant calling, catalogue-based gDST and identified related samples via SNP counting to inform outbreak detection. The lineages and gDST predictions obtained by short-and long-sequencing were compared for all samples as were all putative clusters identified via SNP counting. For convenience Illumina was used as the reference method. FindingsOf the 508 samples, 425 (83.7%) had sufficient read depths to permit comparison between the two sequencing technologies. The assigned lineages were identical for 407/425 (95.8%) samples and all discordances were due to mixed lineages being identified by one technology. Evidence of non-tuberculous mycobacterium (NTM) subpopulations were found in nine samples. Using Illumina as the reference method, the very major error (VME) rate of ONT for predicting resistance to all 15 drugs is 1.0% (0.6-1.5%) whilst the major error (ME) rate is 1.7% (1.3-2.2%) with an unclassified rate of 6.9% (6.3-7.5%). This is below the thresholds specified by the CLSI. Considering each of the 15 drugs individually they had VME and ME point estimates below [≤]3% in 29/30 cases; and most 25/30 below [≤]1.5%. Filtering out all samples containing mixtures left 382 isolates. By appropriate masking of the reference genome we were able to obtain a mean SNP distance between the two platforms of 0.13 (median of zero) for the same sample and for 376/382 samples (98.4%, CI:96.6-99.4%) the difference was [≤]1 SNPs. The high concordance in SNP identification ensured that few differences in the 43 putative clusters among 172 isolates were observed. InterpretationThe differences between the two sequencing platforms for the key clinical outputs is so small that it is now within the tolerances set by regulatory agencies. Provided the sequencing is of sufficient quality, we have therefore reached a threshold whereby sequencing data from long-and short-read platforms can be aggregated. This will enable large scale analyses by national and international public health agencies whilst allowing the MTBC community to take advantage of the portability and speed of long-read sequencing. FundingThe NIHR Health Protection Research Unit: Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford (NIHR200915), a partnership between the UK Health Security Agency (UKHSA) and the University of Oxford, the National Institute for Health and Care Research Biomedical Research Centre: Oxford (BRC) and the Ellison Institute of Technology, Oxford Ltd. The CRyPTIC project was funded by Wellcome [214560/Z/18/Z], a Wellcome Trust/Newton Fund-MRC Collaborative Award (200205/Z/15/Z); and the Bill & Melinda Gates Foundation Trust (OPP1133541). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe conducted a PubMed Central full text search for "tuberculosis" AND ("drug resistance prediction" OR "drug susceptibility prediction") AND ("genome" OR "genomic" OR "geno-typic") AND ("ont" OR "oxford nanopore") between 2022 and 2026 (conducted 1 April 2026). This returned 62 papers; of which, six used both Illumina and ONT sequencing. One of these, published in 2023, directly compared the performance of the two platforms on 151 M. tuberculosis isolates oversampled for resistance. The investigation yielded comparative results for the earlier generation ONT flow cell (R9{middle dot}4{middle dot}1) and base-caller (guppy version 5{middle dot}0{middle dot}16). Another, published in 2026, investigated a targeted next-generation sequencing panel of 20 amplicons using ONT sequencing on R10.4.1 flow cells with guppy 6{middle dot}4{middle dot}6. They compared the results on 71 isolates against phenotypic data and Illumina whole genome sequencing (for 53 isolates) but had low rates of resistance, with all drugs but isoniazid being limited to under five resistant isolates. Two other small studies (10 and 13 samples, respectively) conducted feasibility studies comparing ONT with Illumina, also using earlier generation flow cells and base-calling technology from ONT. Two further studies compared Illumina with ONT for direct sputum sequencing and did not investigate the comparative performance of the two platforms for variant call accuracy, resistance prediction, and outbreak detection. Illumina sequencing technology is widely used for genomic sequence analysis in research, and clinical and public health contexts. Consequently, it has become the de facto reference standard for generating whole genome sequence data. Whilst previous studies established the promise and limitations of long-read (ONT) sequencing as an alternative to short-read sequencing (mainly Illumina), the enhanced performance arising from newer flowcells (e.g. R10.4.1), V14 chemistry, and the latest basecallers (dorado v4.3.0/5.0.0) has not been analysed. Neither has any ONT analysis incorporating the new deep-learning variant callers been evaluated in a large-scale comparative study. Thus, it is currently unclear whether data generated by either platform can be used safely in aggregated analyses for research and clinical or public health service. Added value of this studyWe compared how well short-(Illumina) and long-read (ONT) sequencing platforms identify the genetic variants in M. tuberculosis, predict antituberculous drug resistance and recog-nise outbreaks. The long-reads were generated using the latest generation ONT R10.4.1 flows cells, V14 chemistry, super high accuracy basecalling (dorado v4.3.0/5.0.0) and a bioinformatics analysis pipeline built using the Clair3 deep-learning based variant caller. A total of 508 clinical samples were sequenced using both technologies, substantially more than previous studies. The sampling frame was much larger than previously investigations and included a large proportion of isolates with resistance to first-line and second-line antibiotics as well as bedaquiline. Thus, providing greater statistical power for resistance prediction than before. In particular, the inclusion of bedaquiline resistance provided evidence useful for predicting resistance to this newly deployed drug for treating multi-drug resistant (MDR) TB. We find that the differences between technologies are small meaning that either technology can be used alone safely, and services using both technologies can confidently aggregate the data for analysis. Implications of all the available evidenceThis will be a benefit to local, regional and international organisations, particularly public health agencies, which often have a mix of the two main sequencing technologies for characterising TB whole genome sequences. It also opens up the sequence based diagnostic market to greater competition, particularly if the observed performance can be replicated for other pathogen species.

microbiology↗
bioRxiv2026

Evaluation of an Oxford Nanopore sequencing workflow for mycobacteria from primary MGIT culture

Illumina sequencing of primary MGIT cultures is an established workflow in several reference mycobacteriology laboratories. Oxford Nanopore Technologies (ONT) provides real-time genetic sequencing yielding long reads which help resolve repetitive genomes and is being explored for in-house implementation within diagnostic laboratories. However, low DNA yields from primary MGIT cultures frequently limit the application of ONT workflows, due to high minimum DNA input requirements for library preparation. We validated a modified ONT workflow combining rapid, semi-automated DNA extraction from MGIT cultures with Rapid PCR-Barcoding for whole-genome amplification, and compared its performance with Illumina sequencing for species identification and Mycobacterium tuberculosis complex (MTBC) single-nucleotide polymorphism (SNP) detection. A platform-agnostic analysis pipeline enabled consistent human read removal, taxonomic assignment, and MTBC genomic characterisation. ONT sequencing data was subsampled at 1, 6, and 72 hours to determine the earliest time point for reliable species identification. The concordance between sequencing platforms on species classification was 98.3% (95.8-99.5%) with all differences arising from potential mixed infections. SNP agreement was high, with a mean of 0.3 and a median of 0 SNP differences between sequencing platforms after masking. These findings demonstrate the feasibility of PCR-amplified ONT sequencing as a reliable alternative for routine genomic characterisation of MGIT cultures. IMPORTANCERapid identification of mycobacterial infections is essential for timely patient care and infection control. Many clinical laboratories currently rely on outsourcing sequencing to external reference centres, which adds time and delays the return of clinically actionable results. These services commonly use Illumina sequencing, which, while highly accurate, involves complex workflows and longer turnaround times. Newer technologies offer the potential to generate results in real time, but their use has been limited by the low amount of DNA available from routine culture samples. In this study, we developed an improved workflow that increases the amount of usable DNA and enables reliable, rapid sequencing directly from these samples. This approach allows multiple samples to be processed together and reduces the time needed to obtain results. Importantly, it could enable clinical laboratories to perform sequencing in-house, reducing reliance on external services and improving turnaround times.

molecular biology↗
bioRxiv2025

Rapidly and reproducibly building a comprehensive catalogueof resistance-associated variants for M. tuberculosis

BackgroundCatalogues of genetic variants associated with resistance underpin whole-genome sequencing (WGS)-based predictions of drug susceptibility in Mycobacterium tuberculosis, and are essential for molecular diagnostics and surveillance. The current gold standard catalogues are those released by the WHO but the underlying data are not fully released and they are difficult to interpret. Open and reproducible methods would help address these problems, extending the important work already done. MethodsWe have developed an automated method, catomatic, that uses a binomial test to associate informative isolates with resistance or susceptibility, and built a catalogue (catomatic-1) from the same 39,358 samples used to construct the first edition of the WHO catalogue (WHOv1). We performed a sensitivity analysis to optimise statistical and bioinformatic parameters for each drug, and benchmarked catomatic-1 against WHOv1 using an independent Validation Dataset of 14,380 isolates. FindingsBy using simpler statistics, catomatic-1 algorithmically classified 1,329 genetic variants, ranging from five for linezolid to 440 for pyrazinamide. WHOv1 included generalisable rules added by a panel of experts, increasing its predictive coverage, but at the cost of reproducibility. Despite not including such expert rules, catomatic-1 achieves comparable performance for all drugs, with sensitivities for first-line agents above 88% on the independent Validation Dataset. The automated process allowed us to efficiently explore parameter space; for instance, detecting resistant variants with low read support improved the sensitivity for all drugs. InterpretationPerformant resistance catalogues for M. tuberculosis can be built automatically using transparent and reproducible statistical methods. As more data are collected, catalogue content and performance will evolve, highlighting the need for proper versioning, machine/human readability, and open access. This approach demonstrates resistance catalogues used in surveillance and diagnostics can be rapidly and reproducibily updated. FundingThe National Institute for Health and Care Research (NIHR), Engineering and Physics Sciences Research Council (EPSRC) and ORACLE Corporation. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and preprint servers (bioRxiv, medRxiv), and publicly available mutation catalogues for studies linking Mycobacterium tuberculosis genomic variants with drug resistance using whole-genome or targeted sequencing and phenotypic drug-susceptibility testing (pDST). Search terms combined "Mycobacterium tuberculosis", "genome sequencing", "mutation catalogue", "mutation effects", "drug resistance", and individual drug names, with no language or date restriction. We included studies providing paired, clinical genomic and pDST or MIC data, excluding purely in-silico or case-only reports. This work directly builds on methodologies and data published by five prior studies, and makes primary comparisons with the First (WHOv1) and Second (WHOv2) Editions of the WHO Catalogue of mutations in Mycobacterium tuberculosis. Added value of this studyWe developed catomatic, a transparent, reproducible tool for building catalogues of resistance- and susceptibility-associated genetic variants. Trained on the same samples used to build WHOv1 and benchmarked on an independent Validation Dataset, catomatic achieves comparable sensitivity, specificity, and definitive prediction rates to WHOv1 without expert-rule augmentation and despite using simpler statistics. It optimises parameters per drug, produces machine-readable outputs (CSV/JSON), and demonstrates that adjusting read-support thresholds can improve detection of minor resistance subpopulations. Implications of all the available evidenceCatalogues of resistance-associated variants for M. tuberculosis can be rapidly and transparently constructed. Making catalogues available in human/machine-readable formats with uncertainty estimates will improve uptake of WGS for M. tuberculosis surveillance and diagnostics; using a reproducible process permits diagnostic test manufacturers, researchers, clinical and public health laboratories to select the level of statistical support necessitated by their specific use-case, Policymakers should balance the benefits of expert rules against loss of reproducibility. Future work will expand the size of the datasets used, integrate minimum inhibitory concentration data, and establish consensus workflows for routine, transparent catalogue updates.

microbiology↗
bioRxiv2025

Deacon: fast sequence filtering and contaminant depletion

MotivationRealising the value of large DNA sequence collections demands efficient search and extraction of sequences of interest. Search queries may vary in size from short gene sequences to multiple whole genomes that are too large to fit in computer memory. In microbial genomics, a routine search application involving both large queries and large collections is the removal of contaminating host genome sequences from microbial (meta)genomes. Where the host is human, sensitive classification and excision of host sequences is usually necessary to protect host genetic information. Precise classification is also critical in order to retain microbial sequences and permit accurate microbial genomic analysis. While human pangenomes have been shown to increase sensitivity of human sequence classification, existing bioinformatic host depletion approaches have either limited precision when used with metagenomes or large computing resource requirements. ResultsWe present Deacon, an efficient and versatile sequence filter for raw sequence files and streams. We demonstrate its leading accuracy for the task of host depletion, using less computing resource than existing approaches. By querying a human pangenome index for minimizers contained in each input sequence, Deacon is able to accurately classify and discard diverse human sequences from long reads at over 250Mbp/s with a commodity laptop. We present validation of classification sensitivity, specificity and speed with simulated short and long reads for diverse catalogues of human, bacterial and viral genomes alongside existing methods. Beyond host depletion, Deacon is well suited to common sequence search and filtering applications, particularly those involving large queries. Capable of indexing a human genome in under 30s, Deacon is equipped to rapidly compose custom minimizer indexes using set operations, facilitating efficient search and filtering of massive sequence datasets using gigabase queries. Availability and implementationDeacon is implemented as an MIT-licensed command line tool written in Rust and packaged with Bioconda. Code is available from https://github.com/bede/deacon.

bioinformatics↗
bioRxiv2025

An improved catalogue for whole-genome sequencing prediction of bedaquiline resistance in M. tuberculosis using a reproduciblealgorithmic approach.

Bedaquiline (BDQ) has only been approved for use for a little over a decade yet is a key drug for treating multi-drug resistant tuberculosis, however rising levels of resistance threaten to reduce its effectiveness. Catalogues of mutations associated with resistance to bedaquiline are key to detecting resistance genetically for either diagnosis or surveillance. At present building catalogues requires considerable expert knowledge, often requires the use of complex grading rules, and is an irreproducible process. We developed an automated method, catomatic, that associates genetic variants with resistance (or susceptibility) using a two-tailed binomial test with a stated background rate and applied it to a dataset of 11,867 Mycobacterium tuberculosis samples with whole genome and bedaquline susceptibility testing data. Using this framework we investigated how to best classify variants and the phenotypic significance of minor alleles. The genes mmpS5 and mmpL5 are not directly associated with bedaquline resistance, and our catalogue of Rv0678, atpE, and pepQ variants attains a cross-validated sensitivity and specificity of 79.4 {+/-} 1.8 % and 98.5 {+/-} 0.3%, respectively, for 94 {+/-} 0.4% of samples. Identifying samples with subpopulations containing Rv0678 variants improves sensitivity, and detection thresholds in bioinformatic pipelines should therefore be lowered. By using a more permissive and deterministic algorithm trained on a sufficient number of resistant samples we have reproducibly constructed an AMR catalogue for BDQ resistance-associated variants that is comprehensive and accurate. Impact StatementBedaquiline has recently received global endorsement for tuberculosis treatment, yet the genetic determinants of antimicrobial resistance remain incompletely understood. Existing gold-standard methods for building mutation catalogs lack public accessibility and reproducibility. We introduce catomatic, a reproducible and publicly available method that employs simpler statistics to increase sensitivity to resistance-associated variants. This approach has enabled investigations into mechanisms of resistance, the significance of genetic subpopulations, and key data attributes that influence the ease of classifying effects and the accuracy of BDQ resistance phenotype prediction in clinical samples. We strongly emphasise the utility in using reproducible statistics and sustainably developed software in genetics-focussed microbiology.

microbiology↗
bioRxiv2024

Enhancement and validation of the antibiotic resistance prediction performance of a cloud-based genetics processing platform for Mycobacteria

Tuberculosis remains a global health problem. Making it easier and quicker to identify which antibiotics an infection is likely to be susceptible to will be a key part of the solution. Whilst whole-genome sequencing offers many advantages, the processing of the genetic reads to produce the relevant public health and clinical information is, surprisingly, often the responsibility of the end user which inhibits uptake. Here we characterise how well a freely-available tool we have developed, gnomonicus, predicts the antibiotic resistance profile of a sample (given its variant call file) using our implementation of the second edition of the WHO catalogue of resistance-associated variants (WHOv2). To facilitate this, we have constructed a Diverse Testset of 2,663 publicly-available M. tuberculosis samples which have both genetic and drug susceptibility testing (DST) data. We have chosen to apply the catalogue such that our tool will return a result of (i) Fail if there are insufficient reads at a genetic locus associated with resistance, (ii) Unknown if a genetic variant in a resistance gene not listed in the catalogue is encountered and (iii) Resistant if three or more short-reads support the presence of a resistance-associated variant. The last step increases the sensitivity for all 15 antibiotics but only reaches significance in a few in our testset. Comparing our results to those of TB-Profiler, an existing tool, highlights the different design choices and demonstrates the performance of both tools on our Diverse Testset is comparable. By only considering high confidence DST results we show that gnomonicus, in combination with our translation of WHOv2, achieves sensitivities and specificities in excess of 95% for both isoniazid and rifampicin. Impact StatementWhole genome sequencing clinical samples taken from patients with tuberculosis is a potentially fast and accurate method for determining to which antibiotics the infection will be susceptible. Two barriers need to be overcome; the first, which is knowing which mutations are associated with resistance (or not) to a range of antibiotics is well on the way to be solved thanks to the efforts of the World Health Organization (WHO) who have published extensive catalogues containing lists of such mutations. The second barrier is that the processing of the raw genetic files remains a largely manual process overseen by bioinformaticians. Here we describe gnomonicus, our open-source AMR prediction tool, and report the performance of our translation of the second edition of the WHO catalogue using a carefully designed publicly-available dataset of 2,663 M. tuberculosis samples. We hope that not only will this tool be useful but also that this dataset will be used by other researchers to facilitate comparisons between pipelines, approaches and tools. Data SummaryThe attendant GitHub repository1 allows gnomonicus to be rerun on all 2,663 samples in the Diverse Testset; it therefore includes instructions, the necessary input files (all the variant call files, the version of the WHOv2 catalogue and a link to the H37Rv GenBank file used in this study) and also the output JSON files. The ENA accession numbers for all 2,663 samples (including a bash script to download them) and their corresponding phenotypic drug susceptibility testing results are included with the intention that people can either reproduce our results, or use the same dataset for other analyses. The JSON files output by TB-Profiler have also been added for comparison. The repository contains a series of Juypter notebooks containing Python3 code that allows the user to discover and parse the output JSON files from either tool and save the results as data tables. Other notebooks allow the user to reproduce all the analysis underlying this work, including reproducing the figures and many of the tables.

microbiology↗
bioRxiv2024

Comparison of direct cDNA and PCR-cDNA Nanopore sequencing of Escherichia coli isolates

2.Whole-transcriptome (long-read) RNA sequencing (Oxford Nanopore Technologies, ONT) holds promise for agnostic analysis of differential gene expression (DGE) in pathogenic bacteria, including for antimicrobial resistance genes (ARGs). However, direct cDNA ONT sequencing requires large concentrations of polyadenylated mRNA, and amplification protocols may introduce technical bias. Here we evaluated the impact of direct cDNA and cDNA PCR-based ONT sequencing on transcriptomic analysis of clinical Escherichia coli. Four E. coli bloodstream infection-associated isolates (n=2 biological replicates/isolate) were sequenced using the ONT Direct cDNA Sequencing SQK-DCS109 and PCR-cDNA Barcoding SQK-PCB111.24 kits. Biological and technical replicates were distributed over 8 flow cells using 16 barcodes to minimise batch/barcoding bias. Reads were mapped to a transcript reference and transcript abundance quantified after in silico depletion of low abundance and rRNA genes. We found there were strong correlations between read counts using both kits and when restricting the analysis to include only ARGs. We highlighted correlations were weaker for genes with a higher GC content. Read lengths were longer for the direct cDNA kit compared to the PCR-cDNA kit whereas total yield was higher for the PCR-cDNA kit. In this small but methodologically rigorous evaluation of biological and technical replicates of isolates sequenced with the direct cDNA and PCR-cDNA ONT sequencing kits, we demonstrated that PCR-based amplification substantially improves yield with largely unbiased assessment of core gene and ARG expression. However, users of PCR-based kits should be aware of a small risk of technical bias which appears greater for genes with an unusually high (>52%)/low (<44%) GC-content. 3. Impact statementRNA sequencing allows quantification of RNA within a biological sample providing information on the expression of genes at a particular time. This helps understand the expression of antimicrobial resistance genes (ARGs). In RNA-Seq experimental workflows extra steps of reverse transcription may be needed to generate more stable cDNA to allow for amplification by PCR if starting RNA input was low. Two current methods of long-read RNA sequencing include direct cDNA and PCR-cDNA based sequencing (Oxford Nanopore Technologies, ONT). However, few studies have compared these two methods of RNA-sequencing using clinical bacterial isolates. We therefore undertook a study to compare both kits using a methodological balanced design of biological and technical replicates of E. coli. Our study showed that direct cDNA and PCR-cDNA sequencing is highly reproducible between biological and technical E. coli replicates with very small differences in gene expression signatures generated between kits. The PCR-cDNA kit generates increased sequencing yield but a smaller proportion of mappable reads, the generation of shorter reads of lower quality and some PCR-associated bias. PCR-based amplification greatly increased sequencing yield of core genes and ARGs, however there may be a small risk of PCR-bias in genes that have a higher GC content. 4. Data summaryThe transcript reads of the four sequenced Escherichia coli strains have been deposited in the Figshare, DOI: 10.6084/m9.figshare.25044051. The authors confirm all supporting data (available in Figshare), code (available at: https://github.com/samlipworth/rna_methods) and protocols have been provided within the article or through supplementary data files.

molecular biology↗
bioRxiv2023

Hostile: accurate host decontamination of microbial sequences

MotivationMicrobial sequences generated from clinical samples are often contaminated with human host sequences that must be removed for ethical and legal reasons. Care must be taken to excise host sequences without inadvertently removing target microbial sequences to the detriment of downstream analyses such as variant calling and de novo assembly. ResultsTo facilitate accurate host decontamination of both short and long sequencing reads, we developed Hostile, a tool capable of accurate host read removal using a laptop. We demonstrate that our approach removes at least 99.6% of real human reads and retains at least 99.989% of simulated bacterial reads. Using Hostile with a masked reference genome further increases bacterial read retention (>=99.997%) with negligible (<=0.001%) reduction in human read removal performance. Compared with an existing tool, Hostile removes 21-23% more human short reads and 22-43x fewer bacterial reads with comparable execution time. Availability and implementationHostile is implemented as an MIT licensed Python package available from https://github.com/bede/hostile together with supplementary material.

bioinformatics↗
bioRxiv2022

Genomic Sequencing from Sputum for Tuberculosis Disease Diagnosis, Lineage Determination and Drug Susceptibility Prediction

BackgroundUniversal 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 sample preparation protocols for direct-from-sputum sequencing of Mycobacterium tuberculosis would accelerate access to comprehensive drug susceptibility testing and molecular typing. MethodsWe assessed a thermo-protection buffer-based direct-from-sample M. tuberculosis whole-genome sequencing protocol. We prospectively processed and analyzed 60 acid-fast bacilli smear-positive sputum samples from tuberculosis patients in India and Madagascar. A diversity of semi-quantitative smear positivity level samples 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. ResultsM. tuberculosis was identified from 88% (Illumina), 89% (MinION-monoplex) and 83% (MinION-multiplex) of samples 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 samples on MinION produced higher read depth than Illumina (p<0.05) and MinION multiplex (p<0.01). 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) ConclusionsM. tuberculosis direct-from-sample whole-genome sequencing remains challenging. Improved and affordable sample treatment protocols are needed prior to clinical deployment.

microbiology↗
bioRxiv2022

High-resolution characterisation of short-term temporal variability in the taxonomic and resistome composition of wastewater influent

Wastewater-based epidemiology (WBE) for population-level surveillance of antimicrobial resistance (AMR) is gaining significant traction, but the impact of wastewater sampling methods on results is unclear. In this study we characterised taxonomic and resistome differences between single-timepoint-grab and 24H-composites of wastewater influent from a large UK-based wastewater treatment work (WWTW [population equivalent:223,435]). We autosampled hourly influent grab samples (n=72) over three consecutive weekdays, and prepared additional 24H-composites (n=3) from respective grabs. For taxonomic profiling, metagenomic DNA was extracted from all samples and 16S-rRNA gene sequenced. One composite and six grabs from day one underwent metagenomic sequencing for metagenomic dissimilarity estimation and resistome profiling. Taxonomic abundances of phyla varied significantly across hourly grab samples but followed a repeating diurnal pattern for all three days. Hierarchical clustering grouped grab samples into four time periods dissimilar in both 16S rRNA gene-based profiles and metagenomic distances. 24H-composites resembled mean daily phyla abundances and showed low variability of taxonomic profiles. Of the 122 AMR gene families (AGFs) identified across all day one samples, single grab samples identified a median of 6 (IQR:5-8) AGFs not seen in the composite. However, 36/36 of these hits were at lateral coverage <0.5 (median:0.19; IQR:0.16-0.22) and potential false positives. Conversely, the 24H-composite identified three AGFs not seen in any grab with higher lateral coverage (0.82; 0.55-0.84). Additionally, several clinically significant human AGFs (blaVIM, blaIMP, blaKPC) were intermittently or completely missed by grab sampling but captured by the 24H-composite. Wastewater influent undergoes significant taxonomic and resistome changes on short timescales potentially affecting interpretation of results based on sampling strategy. Grab samples are more convenient and potentially capture low-prevalence/transient targets but are less comprehensive and temporally variable. Therefore, we recommend 24H-composite sampling where feasible. Further validation and optimisation of WBE methods is vital for its development into a robust AMR surveillance approach. HighlightsO_LIInfluent undergoes significant taxonomic/resistome changes over short timescales. C_LIO_LITaxonomic abundances fluctuate diurnally but repeat for the 3 weekdays sampled. C_LIO_LIDetection of less prevalent AMR determinants is time-dependent for grab sampling. C_LIO_LISingle timepoint grab samples may produce temporally variable metagenomic profiles. C_LIO_LI24H-composites reflect mean daily taxa and more reliably captured AMR determinants. C_LI

genomics↗
bioRxiv2022

Penicillin Binding Protein Substitutions Co-occur with Fluoroquinolone Resistance in 'Epidemic Lineages of Multi Drug-Resistant Clostridioides difficile

Clostridioides difficile remains a key cause of healthcare-associated infection, with multi-drug-resistant (MDR) lineages causing high mortality ([&ge;]20%) outbreaks. Cephalosporin treatment is a long-established risk factor, and antimicrobial stewardship a key control. A mechanism underlying raised cephalosporin MICs has not been identified in C. difficile, but among other species resistance is often acquired via amino acid substitutions in cell wall transpeptidases (penicillin binding proteins, PBPs). Here, we investigated five C. difficile transpeptidases (PBP1-5) for recent substitutions. Previously published genome assemblies (n=7096) were obtained, representing sixteen geographically widespread lineages, including healthcare-associated MDR ST1(027), ST3(001) and ST17(018). Recent amino acid substitutions were found within PBP1 (n=50) and PBP3 (n=48), ranging from 1-10 substitutions per genome. {beta}-lactam MICs were measured for closely related pairs of wild-type and PBP substituted isolates separated by 20-273 SNPs. Recombination-corrected, dated phylogenies were constructed to date substitution acquisition. Key substitutions such as PBP3 V497L and PBP1 T674I/N/V emerged independently across multiple lineages. They were associated with extremely high cephalosporin MICs; 1-4 doubling dilutions >wild-type up to [&le;]1506g/ml. Substitution patterns varied by lineage and clade, showed geographic structure, and notably occurred post-1990, coincident with the acquisition of gyrA/B substitutions conferring fluoroquinolone resistance. In conclusion, recent PBP1 and PBP3 substitutions are associated with raised cephalosporin MICs in C. difficile. The co-occurrence of resistance to cephalosporins and fluoroquinolones hinders attempts to understand their relative importance in the dissemination of epidemic lineages. Further controlled studies of cephalosporin and fluoroquinolone stewardship are needed to determine their relative effectiveness in outbreak control. IMPORTANCEFluoroquinolone and cephalosporin prescribing in healthcare settings have triggered outbreaks of high-mortality, multi-drug resistant C. difficile infection. Here, we identify a mechanism of acquired cephalosporin resistance in C. difficile, comprising amino acid substitutions in two cell-wall transpeptidase enzymes (penicillin binding proteins). The higher the number of substitutions, the greater the impact on phenotype. Dated phylogenies revealed that resistance to both cephalosporins and fluoroquinolones was co-acquired immediately before clinically important, outbreak strains emerged. PBP substitutions were geographically structured within genetic lineages, suggesting adaptation to local antimicrobial prescribing. Antimicrobial stewardship of cephalosporins and fluoroquinolones is an effective means of C. difficile outbreak control. Genetic changes conferring resistance likely impart a fitness-cost after antibiotic withdrawal. Our study identifies a mechanism that may explain the contribution of cephalosporin stewardship to resolving outbreak conditions. However, due to the co-occurrence of cephalosporin and fluoroquinolone resistance, further work is needed to determine the relative importance of each.

microbiology↗
bioRxiv2022

Evaluation of metagenomic, 16S rRNA gene and ultra-plexed PCR-based sequencing approaches for profiling antimicrobial resistance gene and bacterial taxonomic composition of polymicrobial samples

BackgroundShotgun metagenomic sequencing is increasingly popular in taxonomic and resistome-profiling of polymicrobial samples due to its agnostic nature and data versatility. However, caveats include high- cost, sequencing depth/sensitivity trade-offs, and challenging bioinformatic deconvolution. Targeted PCR-based profiling optimises sensitivity and cost-effectiveness, but can only identify prespecified targets and may introduce amplification biases. Ultra-high multiplexed PCR is a potential compromise. As no comprehensive comparative evaluation exists, we evaluated performance of each method in taxonomic/resistome-profiling of a well-defined DNA mock sample and seven "real- world" wastewater samples. ResultsWe tested three sequencing approaches (short-read shotgun metagenomics, Illumina Ampliseq ultra-plexed AMR Research Panel, 16S rRNA gene sequencing) with seven bioinformatic pipelines (ResPipe, Illumina DNA Amplicon App, One Codex Metagenomic-/Targeted Loci classification and Ampliseq Report, DADA2, and an in-house pipeline for AmpliSeq data [AmpliSeek]). Metagenomics outperformed 16S rRNA gene sequencing in accurately reconstituting a mock taxonomic profile and optimising the identification of diverse wastewater taxa, while 16S rRNA gene sequencing produced more even taxonomic outputs which may be quantitatively inaccurate but enhance detection of low abundance taxa. Shotgun metagenomic and AmpliSeq sequencing performed equally well in profiling AMR genes present in a mock sample, but AmpliSeq identified more genes in more complex, "real-world" samples, likely related to sensitivity of detection at the metagenomic sequencing depth used. ConclusionsA complementary sequencing approach employing 16S rRNA gene or shallow-metagenomic sequencing for taxonomic profiling, and the AmpliSeq AMR panel for high-resolution resistome profiling represents a potential lower-cost alternative to deep shotgun sequencing and may also be more sensitive for the detection of low-prevalence AMR genes. However, our evaluation highlights that both the sequencing and bioinformatics approach used can significantly influence results; for AmpliSeq AMR gene profiling, we developed AmpliSeek which outperformed the other pipelines tested and is open source. Sequencing approach and bioinformatic pipeline should be considered in the context of study goals and sample type, with study-specific validation when feasible.

genomics↗
bioRxiv2022

Plasmid overlap and evolution between Enterobacterales isolates from bloodstream infections and non-human compartments

Plasmids enable the dissemination of antimicrobial resistance (AMR) in common Enterobacterales pathogens, representing a major public health challenge. However, the extent of plasmid sharing and evolution between Enterobacterales causing human infections and other niches remains unclear, including the emergence of resistance plasmids. Dense, unselected sampling is highly relevant to developing our understanding of plasmid epidemiology and designing appropriate interventions to limit the emergence and dissemination of plasmid-associated AMR. We established a geographically and temporally restricted collection of human bloodstream infection (BSI)-associated, livestock-associated (cattle, pig, poultry, and sheep faeces, farm soils) and wastewater treatment work (WwTW)-associated (influent, effluent, waterways upstream/downstream of effluent outlets) Enterobacterales. Isolates were collected between 2008-2020 from sites <60km apart in Oxfordshire, UK. Pangenome analysis of plasmid clusters revealed shared "backbones", with phylogenies suggesting an intertwined ecology where well-conserved plasmid backbones carry diverse accessory functions, including AMR genes. Many plasmid "backbones" were seen across species and niches, raising the possibility that plasmid movement between these followed by rapid accessory gene change could be relatively common. Overall, the signature of identical plasmid sharing is likely to be a highly transient one, implying that plasmid movement might be occurring at greater rates than previously estimated, raising a challenge for future genomic One Health studies. FundingThis study was funded by the Antimicrobial Resistance Cross-council Initiative supported by the seven research councils and the NIHR, UK.

genomics↗
bioRxiv2022

Comparison of R9.4.1/Kit10 and R10/Kit12 Oxford Nanopore flowcells and chemistries in bacterial genome reconstruction

2.Complete, accurate, cost-effective, and high-throughput reconstruction of bacterial genomes for large-scale genomic epidemiological studies is currently only possible with hybrid assembly, combining long- (typically using nanopore sequencing) and short-read (Illumina) datasets. Being able to utilise nanopore-only data would be a significant advance. Oxford Nanopore Technologies (ONT) have recently released a new flowcell (R10.4) and chemistry (Kit12), which reportedly generate per-read accuracies rivalling those of Illumina data. To evaluate this, we sequenced DNA extracts from four commonly studied bacterial pathogens, namely Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus, using Illumina and ONTs R9.4.1/Kit10, R10.3/Kit12, R10.4/Kit12 flowcells/chemistries. We compared raw read accuracy and assembly accuracy for each modality, considering the impact of different nanopore basecalling models, commonly used assemblers, sequencing depth, and the use of duplex versus simplex reads. "Super accuracy" (sup) basecalled R10.4 reads - in particular duplex reads - have high per-read accuracies and could be used to robustly reconstruct bacterial genomes without the use of Illumina data. However, the per-run yield of duplex reads generated in our hands with standard sequencing protocols was low (typically <10%), with substantial implications for cost and throughput if relying on nanopore data only to enable bacterial genome reconstruction. In addition, recovery of small plasmids with the best-performing long-read assembler (Flye) was inconsistent. R10.4/Kit12 combined with sup basecalling holds promise as a singular sequencing technology in the reconstruction of commonly studied bacterial genomes, but hybrid assembly (Illumina+R9.4.1 hac) currently remains the highest throughput, most robust, and cost-effective approach to fully reconstruct these bacterial genomes. 3. Impact statementOur understanding of microbes has been greatly enhanced by the capacity to evaluate their genetic make-up using a technology known as whole genome sequencing. Sequencers represent microbial genomes as stretches of shorter sequence known as reads, which are then assembled using computational algorithms. Different types of sequencing approach have advantages and disadvantages with respect to the accuracy and length of the reads they generate; this in turn affects how reliably genomes can be assembled. Currently, to completely reconstruct bacterial genomes in a high-throughput and cost-effective manner, researchers tend to use two different types of sequencing data, namely Illumina (short-read) and nanopore (long-read) data. Illumina data are highly accurate; nanopore data are much longer, and this combination facilitates accurate and complete bacterial genomes in a so-called "hybrid assembly". However, new developments in nanopore sequencing have reportedly greatly improved the accuracy of nanopore data, hinting at the possibility of requiring only a single sequencing approach for bacterial genomics. Here we evaluate these improvements in nanopore sequencing in the reconstruction of four bacterial reference strains, where the true sequence is already known. We show that although these improvements are extremely promising, for high-throughput, low-cost complete reconstruction of bacterial genomes hybrid assembly currently remains the optimal approach. 4. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article, through supplementary data files, or in publicly accessible repositories. Nanopore fast5 and fastq data are available in the ENA under project accession: PRJEB51164. Assemblies have been made available at: https://figshare.com/articles/online_resource/q20_comparison_genome_assemblies/196838 67. Code and analysis outputs are available at: https://gitlab.com/ModernisingMedicalMicrobiology/assembly_comparison_analysis/-/tree/main (tagged version v0.5.5).

genomics↗
bioRxiv2021

BashTheBug: a crowd of volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates.

Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, thereby determining the minimum inhibitory concentration (MIC) of each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is an expensive and slow process that requires highly-skilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing.

microbiology↗
bioRxiv2021

Flanker: a tool for comparative genomics of gene flanking regions

Analysing the flanking sequences surrounding genes of interest is often highly relevant to understanding the role of mobile genetic elements (MGEs) in horizontal gene transfer, particular for antimicrobial resistance genes. Here, we present Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of MGEs without prior knowledge of their structure. These clusters, known as flank patterns, are based on Mash distances, allowing for easy comparison of similarity across sequences. Additionally, Flanker can be flexibly parameterised to finetune outputs by characterising upstream and downstream regions separately and investigating variable lengths of flanking sequence. We apply Flanker to two recent datasets describing plasmid-associated carriage of important carbapenemase genes (blaOXA-48 and blaKPC-2/3) and show that it successfully identifies distinct clusters of flank patterns, including both known and previously uncharacterised structural variants. For example, Flanker identified four Tn4401 profiles that could not be sufficiently characterised using TETyper or MobileElementFinder, demonstrating the utility of Flanker for flanking gene characterisation. Similarly, using a large (n=226) European isolate dataset, we confirm findings from a previous smaller study demonstrating association between Tn1999.2 and blaOXA-48 upregulation and demonstrate 17 flank patterns (compared to the 5 previously identified). More generally the demonstration in this study that flank patterns are associated with to geographical regions and antibiotic susceptibility phenotypes suggests that they may be useful as epidemiological markers. Flanker is freely available under an MIT license at https://github.com/wtmatlock/flanker. Data SummaryNCBI accession numbers for all sequencing data used in this study is provided in Supplementary Table 1. The analysis performed in this manuscript can be reproduced in a binder environment provided on the Flanker Github page (https://github.com/wtmatlock/flanker).

bioinformatics↗
bioRxiv2021

Transmission of pre-XDR and XDR-TB in the Mumbai Metropolitan Region, India

Multidrug-resistant (MDR) and extensively drug resistant (XDR) Mycobacterium tuberculosis complex (MTBC) strains are a great challenge for tuberculosis (TB) control in India. Still, factors driving the MDR/XDR epidemic in India are not well defined. To address this, whole genome sequencing (WGS) data from 1 852 MTBC strains obtained from patients from a tertiary care hospital laboratory in Mumbai were used for phylogenetic strain classification, resistance prediction, and cluster analysis (12 allele distance threshold). Factors associated with pre-XDR/XDR-TB were defined by odds ratios and a multivariate logistic regression model. Overall, 1 017 MTBC strains were MDR, out of which 57.8 % (n=591) were pre-XDR, and 17.9 % (n=183) were XDR. Lineage 2 (L2) strains represented 41.7 % of the MDR, 77.2 % of the pre-XDR, and 86.3 % of the XDR strains, and were significantly associated with pre-XDR/XDR-TB (P < 0.001). Cluster rates were high among MDR (78 %) and pre-XDR/XDR (85 %) strains with three dominant L2 strain clusters (Cl 1-3) representing half of the pre-XDR and two thirds of the XDR-TB cases. Cl 1 strains accounted for 52.5 % of the XDR MTBC strains. Transmission could be confirmed by identical mutation patterns of particular pre-XDR/XDR strains. As a conclusion high rates of pre-XDR/XDR strains among MDR-TB patients require rapid changes in treatment and control strategies. Transmission of particular pre-XDR/XDR L2 strains is the main driver of the pre-XDR/XDR-TB epidemic. Accordingly, control of the epidemic in the region requires measures with stopping transmission especially of pre-XDR/XDR L2 strains.

molecular biology↗
bioRxiv2020

The unintended consequences of a surge in antibiotic resistance when removing wastewater drain biofilm

The prevalence and proliferation of antimicrobial resistant bacteria is considered one of the critical issues of our time. Wastewater is a habitat for complex microbial communities where bacteria share genes of antimicrobial resistance through horizontal gene transfer. Hospital wastewater drainage systems are an ideal reservoir for environmental and pathogenic bacteria to interface and exchange genes of antimicrobial resistance1. Highly resistant Enterobacterales are of the greatest concern because they not only cause human infections but can also thrive in the environment2,3 and have shown to transmit from sink drains to patients4. Replacement of contaminated plumbing may be the most intuitive and widely deployed response once highly resistant potentially pathogenic bacteria are identified in a sink drain. Here we show using shotgun metagenomic sequencing of sink drain biofilms (in 6 intensive care patient rooms, 36 subsamples) paired with microbial culture analysis, an evident shift of biofilm community structure towards increased abundance of Enterobacteriaceae in the newly replaced sink plumbing. Significant increase in resistome load and abundance of clinically relevant resistance and typically mobile genes in the newly replaced plumbing was also observed. Findings from this study demonstrate that exchanging contaminated plumbing for new plumbing may actually have the unexpected consequence of increased abundance of Enterobacterales and genes of antimicrobial resistance in the sink drains. Disruption of preexisting complex environmental biofilms may result in an unintended increase in the amount of antimicrobial resistant Enterobacterales which are targeted for elimination. Temporal variability is an important attribute of ecosystems affecting colonization dynamics and biotic interactions (composition of introduced and resident communities) are key to functional outcomes. Absence of competition within an ecosystem favors invasion.

microbiology↗