Biology subjects

Eyre, D. W.

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

16 recordsLinked to original sources

bioRxiv2026

OxBreaker: species-agnostic pipeline for the analysis of outbreaks using nanopore sequencing

Real-time genomic surveillance may mitigate the spread of health-care-associated infections, but whole-genome sequencing costs and the need for specialised expertise constrain its wide implementation in public health. Here we present OxBreaker, an automated and species-agnostic pipeline optimised for the high-resolution analysis of bacterial and plasmid genomes sequenced via Oxford Nanopore Technologies (ONT). OxBreaker streamlines the transition from raw reads to phylogenetic inference through automated reference selection and high-accuracy variant calling. It is accessible via a graphical user interface (GUI) that can be easily installed locally and operated by non-specialists. Benchmarking against technical and biological replicates of high-priority pathogens demonstrates high accuracy, with false positive variant rates reduced to 0-4 single-nucleotide polymorphisms (SNPs) for common species. We further validated the pipeline by accurately characterising previously published clonal and plasmid-mediated outbreaks, reproducing established phylogenies with improved accessibility. By providing a stable, scalable, open-source offline-compatible solution that matches the resolution of short-read platforms while maintaining the speed of long-read technology, OxBreaker is designed to facilitate the adoption of local, real-time genomic surveillance for frontline infection prevention and control.

genomics↗

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↗

bioRxiv2024

Genomic epidemiology of Candida auris introduction and outbreaks in the United Kingdom

BackgroundCandida auris is a globally emerging fungal pathogen that causes nosocomial invasive infections, particularly in intensive care units (ICU). Four prominent genetic clades originating from distinct geographic regions have been identified: South Asia (Clade I), East Asia (Clade II), Africa (Clade III) and South America (Clade IV) with each clade presenting differing antifungal resistance profiles. We aimed to elucidate the epidemiology of this infection in the United Kingdom (UK) 2014 - 2019 using genomic approaches. MethodsGenome sequences from 24 isolates from six patients in four London hospitals were combined with genome sequences from 183 additional outbreak isolates from nine UK hospitals. These data were used to assess the numbers and timings of C. auris lineage introductions into the UK and to infer subsequent patterns of inter- and intra-hospital transmission. FindingsWe found evidence for at least three introductions of C. auris into the UK, one from Clade I and one from Clade III. The evolutionary rate of C. auris Clade I and Clade III were estimated at 2.764 x 10-4 and 3.186 x 10-4 substitutions per polymorphic site per year, respectively, with entry into the UK as 2013 and 2016 for Clades I and III respectively. We observed temporal and geographical evidence for multiple transmission events between hospitals and identified local within-hospital patient-to-patient transmission events. InterpretationThese data confirm that C. auris is a newly emerged infection in the UK with at least three original introductions into this country. Our analysis shows that hospital outbreaks are linked and confirms that transmission amongst patients has occurred, explaining local hospital outbreaks. Our findings argue that enhanced surveillance of C. auris infection within the UK is necessary in order to protect healthcare and to curtail expansion of this emerging infection. FundingThis work was supported by a Wellcome Trust Institutional Strategic Support Fund Springboard Fellowship, and by the Medical Research Council (MR/R015600/1), the Natural Environment Research Council (NE/P001165/1) and the Wellcome Trust (219551/Z/19/Z). Research in contextSince its first description in 2009, Candida auris has spread across the globe. For this study, authors considered all publications describing whole genome sequences of isolates within the UK up until 2020 to assess the genomic epidemiology of this fungal pathogen. This study adds value to the current understanding of C. auris epidemiology by undertaking the first analysis to assess transmission between and within hospitals using genomic data. We also provide the first in-depth temporal analysis to estimate likely times of introduction into the UK. These results have clinical implications, encouraging hospitals to identify yeast upon admission and to assess multiple isolates from single patients, which may harbour much diversity in terms of genetics and drug resistance.

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 ([≥]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 [≤]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

Benchmarking taxonomic classifiers with Illumina and Nanopore sequence data for clinical metagenomic diagnostic applications

Culture-independent metagenomic detection of microbial species has the potential to provide rapid and precise real-time diagnostic results. However, it is potentially limited by sequencing and classification errors. We use simulated and real-world data to benchmark rates of species misclassification using 100 reference genomes for each of ten common bloodstream pathogens and six frequent blood culture contaminants (n=1600). Simulating both with and without sequencing error for both the Illumina and Oxford Nanopore platforms, we evaluated commonly used classification tools including Kraken2, Bracken, and Centrifuge, utilising mini (8GB) and standard (30-50GB) databases. Bracken with the standard database performed best, the median percentage of reads across both sequencing platforms identified correctly to the species level was 98.46% (IQR 93.0:99.3) [range 57.1:100]. For Kraken2 with a mini database, a commonly used combination, median species-level identification was 79.3% (IQR 39.1:88.8) [range 11.2:100]. Classification performance varied by species, with E. coli being more challenging to classify correctly (59.4% to 96.4% reads with correct species, varying by tool used). By filtering out shorter Nanopore reads (<3500bp) we found performance similar or superior to Illumina sequencing, despite higher sequencing error rates. Misclassification was more common when the misclassified species had a higher average nucleotide identity to the true species. Our findings highlight taxonomic misclassification of sequencing data occurs and varies by sequencing and analysis workflow. This "bioinformatic contamination" should be accounted for in metagenomic pipelines to ensure accurate results that can support clinical decision making. ImportanceMetagenomics may transform clinical microbiology by enabling more rapid species detection in a potentially unbiased manner and reducing reliance on culture-based approaches. However, it is still limited by ongoing challenges such as sequencing and classification software errors. In this study, we use simulated and real-world data to define the intrinsic rates of species misclassification that occur using Illumina and Oxford Nanopore sequencing platforms with commonly used taxonomic classification tools and databases. We quantify the extent of "bioinformatic contamination" arising from the classification process. This enables us to identify the best performing tools that maximize classification accuracy, and to suggest how taxonomic misclassification can be formally accounted for in clinical diagnostic workflows. Specifically, we specify thresholds for identifying or excluding polymicrobial infections in metagenomic samples, based on rates of misclassification of similar species, which might have clinical implications when treating infection.

microbiology↗

bioRxiv2021

Performance of Core Genome Multilocus Sequence Typing Compared to Capillary-Electrophoresis PCR Ribotyping and SNP Analysis of Clostridioides difficile

Clostridioides difficile is the most common cause of antibiotic-associated gastrointestinal infections. Capillary-electrophoresis (CE)-PCR ribotyping is currently the gold standard for C. difficile typing but lacks discriminatory power to study transmission and outbreaks in detail. New molecular methods have the capacity to differentiate better, but backward compatibility with CE-PCR ribotyping must be assessed. Using a well-characterized collection of diverse strains (N=630; 100 unique ribotypes [RTs]), we aimed to investigate PCR ribotyping prediction from core genome multilocus sequence typing (cgMLST). Additionally, we compared the discriminatory power of cgMLST (SeqSphere & EnteroBase) and whole genome MLST (wgMLST) (EnteroBase) with single nucleotide polymorphism (SNP) analysis). A unique cgMLST profile (>6 allele differences) was observed in 82/100 ribotypes, indicating sufficient backward compatibility. Intra-RT allele difference varied per ribotype and MLST clade. Application of cg/wgMLST and SNP analysis in two outbreak settings with ribotypes RT078 and RT181 (known with a low intra-ribotype allele difference) showed no distinction between outbreak- and non-outbreak strains, in contrast to wgMLST and SNP analysis. We conclude that cgMLST has the potential to be an alternative to CE-PCR ribotyping. The method is reproducible, easy to standardize and offers higher discrimination. However, in some ribotype complexes adjusted cut-off thresholds and epidemiological data are necessary to recognize outbreaks. We propose to decrease the current threshold of 6 to 3 alleles to better identify outbreaks.

molecular biology↗

bioRxiv2021

K-mer based prediction of Clostridioides difficile relatedness and ribotypes

Comparative analysis of Clostridioides difficile whole-genome sequencing (WGS) data enables fine scaled investigation of transmission and is increasingly becoming part of routine surveillance. However, these analyses are constrained by the computational requirements of the large volumes of data involved. By decomposing WGS reads or assemblies into k-mers and using the dimensionality reduction technique MinHash, it is possible to rapidly approximate genomic distances without alignment. Here we assessed the performance of MinHash, as implemented by sourmash, in predicting single nucleotide differences between genomes (SNPs) and C. difficile ribotypes (RTs). For a set of 1,905 diverse C. difficile genomes (differing by 0-168,519 SNPs), using sourmash to screen for closely related genomes, at a sensitivity of 100% for pairs [≤]10 SNPs, sourmash reduced the number of pairs from 1,813,560 overall to 161,934, i.e., by 91%, with a positive predictive value of 32% to correctly identify pairs [≤]10 SNPs (maximum SNP distance 4,144). At a sensitivity of 95%, pairs were reduced by 94% to 108,266 and PPV increased to 45% (maximum SNP distance 1,009). Increasing the MinHash sketch size above 2000 produced minimal performance improvement. We also explored a MinHash similarity-based ribotype prediction method. Genomes with known ribotypes (n=3,937) were split into a training set (2,937) and test set (1,000) randomly. The training set was used to construct a sourmash index against which genomes from the test set were compared. If the closest 5 genomes in the index had the same ribotype this was taken to predict the searched genomes ribotype. Using our MinHash ribotype index, predicted ribotypes were correct in 780/1000 (78%) genomes, incorrect in 20 (2%), and indeterminant in 200 (20%). Relaxing the classifier to 4/5 closest matches with the same RT improved the correct predictions to 87%. Using MinHash it is possible to subsample C. difficile genome k-mer hashes and use them to approximate small genomic differences within minutes, significantly reducing the search space for further analysis. Impact statementThe genetic code, or DNA, of bacteria is increasingly used to track how infection spreads and to guide infection control interventions, as similar or identical DNA sequences are expected in samples from pair of individuals related by transmission. While obtaining the DNA sequence for bacteria is increasingly straightforward, comparing thousands or even millions of sequences requires substantial computing power and time using current approaches. Here we describe how a method for summarising sequencing data, MinHash, can be used to rapidly reduce the number of possible close sequence matches in Clostridioides difficile, an important healthcare-associated pathogen. It can also be used to approximate traditional schemes used to classify C. difficile into smaller subgroups in transmission analyses, such as ribotyping. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

genomics↗

bioRxiv2020

The Clostridioides difficile species problem: global phylogenomic analysis uncovers three ancient, toxigenic, genomospecies

Clostridioides difficile infection (CDI) remains an urgent global One Health threat. The genetic heterogeneity seen across C. difficile underscores its wide ecological versatility and has driven the significant changes in CDI epidemiology seen in the last 20 years. We analysed an international collection of over 12,000 C. difficile genomes spanning the eight currently defined phylogenetic clades. Through whole-genome average nucleotide identity, pangenomic and Bayesian analyses, we identified major taxonomic incoherence with clear species boundaries for each of the recently described cryptic clades CI-III. The emergence of these three novel genomospecies predates clades C1-5 by millions of years, rewriting the global population structure of C. difficile specifically and taxonomy of the Peptostreptococcaceae in general. These genomospecies all show unique and highly divergent toxin gene architecture, advancing our understanding of the evolution of C. difficile and close relatives. Beyond the taxonomic ramifications, this work impacts the diagnosis of CDI worldwide.

microbiology↗

bioRxiv2020

High precision Neisseria gonorrhoeae variant and antimicrobial resistance calling from metagenomic Nanopore sequencing

The rise of antimicrobial resistant Neisseria gonorrhoeae is a significant public health concern. Against this background, rapid culture-independent diagnostics may allow targeted treatment and prevent onward transmission. We have previously shown metagenomic sequencing of urine samples from men with urethral gonorrhoea can recover near-complete N. gonorrhoeae genomes. However, disentangling the N. gonorrhoeae genome from metagenomic samples and robustly identifying antimicrobial resistance determinants from error-prone Nanopore sequencing is a substantial bioinformatics challenge. Here we demonstrate an N. gonorrhoeae diagnostic workflow for analysis of metagenomic sequencing data obtained from clinical samples using R9.4.1 Nanopore sequencing. We compared results from simulated and clinical infections with data from known reference strains and Illumina sequencing of isolates cultured from the same patients. We evaluated three Nanopore variant callers and developed a random forest classifier to filter called SNPs. Clair was the most suitable variant caller after SNP filtering. A minimum depth of 20x reads was required to confidently identify resistant determinants over the entire genome. Our findings show that metagenomic Nanopore sequencing can provide reliable diagnostic information in N. gonorrhoeae infection.

microbiology↗

bioRxiv2019

Optimizing DNA extraction methods for Nanopore sequencing of Neisseria gonorrhoeae direct from urine samples

BackgroundEmpirical gonorrhoea treatment at initial diagnosis reduces onward transmission. However, increasing resistance to multiple antibiotics may necessitate waiting for culture-based diagnostics to select an effective treatment. There is a need for same-day culture-free diagnostics that identify infection and detect antimicrobial resistance.\n\nMethodsWe investigated if Nanopore sequencing can detect sufficient N. gonorrhoeae DNA to reconstruct whole genomes directly from urine samples. We used N. gonorrhoeae spiked urine samples and samples from gonorrhoea infections to determine optimal DNA extraction methods that maximize the amount of N. gonorrhoeae DNA sequenced whilst minimizing contaminating host DNA.\n\nResultsIn simulated infections the Qiagen UCP Pathogen Mini kit provided the highest ratio N. gonorrhoeae to human DNA and the most consistent results. Depletion of human DNA with saponin increased N. gonorrhoeae yields in simulated infections, but decreased yields in clinical samples. In ten urine samples from men with symptomatic urethral gonorrhoea, [≥]87% coverage of an N. gonorrhoeae reference genome was achieved in all samples, with [≥]92% coverage breath at [≥]10-fold depth in 7 (70%) samples. In simulated infections if [≥]104 CFU/ml of N. gonorrhoeae was present, sequencing of the large majority of the genome was frequently achieved. N. gonorrhoeae could also be detected from urine in cobas PCR Media tubes and from urethral swabs, and in the presence of simulated Chlamydia co-infection.\n\nConclusionUsing Nanopore sequencing of urine samples from men with urethral gonorrhoea sufficient data can be obtained to reconstruct whole genomes in the majority of samples without the need for culture.

microbiology↗

bioRxiv2019

Hash-based core genome multi-locus sequencing typing for Clostridium difficile

BackgroundPathogen whole-genome sequencing has huge potential as a tool to better understand infection transmission. However, rapidly identifying closely-related genomes among a background of thousands of other genomes is challenging.\n\nMethodsWe describe a refinement to core-genome multi-locus sequence typing (cgMLST) where alleles at each gene are reproducibly converted to a unique hash, or short string of letters (hash-cgMLST). This avoids the resource-intensive need for a single centralised database of sequentially-numbered alleles. We test the reproducibility and discriminatory power of cgMLST/hash-cgMLST compared to mapping-based approaches in Clostridium difficile using repeated sequencing of the same isolates (replicates) and data from consecutive infection isolates from six English hospitals.\n\nResultsHash-cgMLST provided the same results as standard cgMLST with minimal performance penalty. Comparing 272 pairs of replicate sequences, using reference-based mapping there were 0, 1 or 2 SNPs between 262(96%), 5(2%) and 1(<1%) pairs respectively. Using hash-cgMLST or standard cgMLST, 197(72%) replicate pairs had zero gene differences, 37(14%), 8(3%) and 30(11%) pairs had 1, 2 and >2 differences respectively. False gene differences were clustered in specific genes and associated with fragmented assemblies. Considering 413 pairs of infections within [≤]2 SNPS, i.e. consistent with recent transmission, 266(64%) had [≤]2 gene differences and 50(12%) [≥]5 differences. Comparing a genome to 100,000 others took <1 minute using hash-cgMLST.\n\nConclusionHash-cgMLST is an effective surveillance tool that can rapidly identify clusters of related genomes. However, cgMLST/hash-cgMLST generates potentially more false variants than mapping-based analysis. Refined mapping-based variant calling is likely required to precisely define close genetic relationships.

microbiology↗

bioRxiv2019

Genomic diversity affects the accuracy of bacterial SNP calling pipelines

BackgroundAccurately identifying SNPs from bacterial sequencing data is an essential requirement for using genomics to track transmission and predict important phenotypes such as antimicrobial resistance. However, most previous performance evaluations of SNP calling have been restricted to eukaryotic (human) data. Additionally, bacterial SNP calling requires choosing an appropriate reference genome to align reads to, which, together with the bioinformatic pipeline, affects the accuracy and completeness of a set of SNP calls obtained.\n\nThis study evaluates the performance of 41 SNP calling pipelines using simulated data from 254 strains of 10 clinically common bacteria and real data from environmentally-sourced and genomically diverse isolates within the genera Citrobacter, Enterobacter, Escherichia and Klebsiella.\n\nResultsWe evaluated the performance of 41 SNP calling pipelines, aligning reads to genomes of the same or a divergent strain. Irrespective of pipeline, a principal determinant of reliable SNP calling was reference genome selection. Across multiple taxa, there was a strong inverse relationship between pipeline sensitivity and precision, and the Mash distance (a proxy for average nucleotide divergence) between reads and reference genome. The effect was especially pronounced for diverse, recombinogenic, bacteria such as Escherichia coli, but less dominant for clonal species such as Mycobacterium tuberculosis.\n\nConclusionsThe accuracy of SNP calling for a given species is compromised by increasing intra-species diversity. When reads were aligned to the same genome from which they were sequenced, among the highest performing pipelines was Novoalign/GATK. However, across the full range of (divergent) genomes, among the consistently highest-performing pipelines was Snippy.

bioinformatics↗

bioRxiv2018

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

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

microbiology↗

bioRxiv2017

Real-time analysis of nanopore-based metagenomic sequencing from orthopaedic device infection

Prosthetic joint infections are clinically difficult to diagnose and treat. Previously, we demonstrated metagenomic sequencing on an Illumina MiSeq replicates the findings of current gold standard microbiological diagnostic techniques. Nanopore sequencing offers advantages in speed of detection over MiSeq. Here, we compare direct-from-clinical-sample metagenomic Illumina sequencing with Nanopore sequencing, and report a real-time analytical pathway for Nanopore sequence data, designed for detecting bacterial composition of prosthetic joint infections.\n\nDNA was extracted from the sonication fluids of seven explanted orthopaedic devices, and additionally from two culture negative controls, and was sequenced on the Oxford Nanopore Technologies MinION platform. A specific analysis pipeline was assembled to overcome the challenges of identifying the true infecting pathogen, given high levels of host contamination and unavoidable background lab and kit contamination.\n\nThe majority of DNA classified (>90%) was host contamination and discarded. Using negative control filtering thresholds, the species identified corresponded with both routine microbiological diagnosis and MiSeq results. By analysing sequences in real time, causes of infection were robustly detected within minutes from initiation of sequencing.\n\nWe demonstrate initial proof of concept that metagenomic MinION sequencing can provide rapid, accurate diagnosis for prosthetic joint infections. We demonstrate a novel, scalable pipeline for real-time analysis of MinION sequence data. The high proportion of human DNA in extracts prevents full genome analysis from complete coverage, and methods to reduce this could increase genome depth and allow antimicrobial resistance profiling.

microbiology↗

bioRxiv2017

Molecular diagnosis of orthopaedic device infection direct from sonication fluid by metagenomic sequencing

Culture of multiple periprosthetic tissue samples is the current gold-standard for microbiological diagnosis of prosthetic joint infections (PJI). Additional diagnostic information may be obtained through sonication fluid culture of explants. However, current techniques can have relatively low sensitivity, with prior antimicrobial therapy and infection by fastidious organisms influencing results. We assessed if metagenomic sequencing of complete bacterial DNA extracts obtained direct from sonication fluid can provide an alternative rapid and sensitive tool for diagnosis of PJI.\n\nWe compared metagenomic sequencing with standard aerobic and anaerobic culture in 97 sonication fluid samples from prosthetic joint and other orthopaedic device infections. Reads from Illumina MiSeq sequencing were taxonomically classified using Kraken. Using 50 samples (derivation set), we determined optimal thresholds for the number and proportion of bacterial reads required to identify an infection and validated our findings in 47 independent samples.\n\nCompared to sonication fluid culture, the species-level sensitivity of metagenomic sequencing was 61/69(88%,95%CI 77-94%) (derivation samples 35/38[92%,79-98%]; validation 26/31[84%,66-95%]), and genus-level sensitivity was 64/69(93%,84-98%). Species-level specificity, adjusting for plausible fastidious causes of infection, species found in concurrently obtained tissue samples, and prior antibiotics, was 85/97(88%,79-93%) (derivation 43/50[86%,73-94%], validation 42/47[89%,77-96%]). High levels of human DNA contamination were seen despite use of laboratory methods to remove it. Rigorous laboratory good practice was required to prevent bacterial DNA contamination.\n\nWe demonstrate metagenomic sequencing can provide accurate diagnostic information in PJI. Our findings combined with increasing availability of portable, random-access sequencing technology offers the potential to translate metagenomic sequencing into a rapid diagnostic tool in PJI.

microbiology↗