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Stoesser, N.

Publications and source records attributed to Stoesser, N..

At least 19 recordsLinked to original sources

Global genomic epidemiology of multi-carbapenemase Enterobacterales

Enterobacterales pathogens that encode multiple carbapenemase genes are an emerging public health threat. The genomic and plasmid context of the multi-carbapenemase producers has not yet been explored at scale. We analysed 1501 publicly-available global genomes that encoded two or more genes from the five prevalent carbapenemase families (IMP, KPC, NDM, OXA-48-like, and VIM). We observed 241 distinct allelic combinations, with NDM/OXA-48-like (25.6%), multiple KPC (25.3%), KPC/NDM (18.8%), and multiple NDM (10.9%) being the most common groups. We found that many genomes were part of high-risk lineages (48.0%). Most genomes carried carbapenemase genes on two plasmids (59.2%) or one plasmid (23.5%), and most genomes encoded different carbapenemase families (56.2%) rather than copies of the same allele (36.2%). We observed multiple mechanisms of multi-carbapenemase evolution including plasmid co-integration, convergence with virulence, and generation of novel allele diversity through duplication. Multi-carbapenemase plasmids had more AMR genes that conferred resistance to more AMR classes compared to plasmids encoding a single carbapenemase. The proportion of cross-class combinations (KPC/NDM and NDM/OXA-48-like) increased significantly over time, with NDM-5/OXA-181 (3.3-fold) and NDM-4/OXA-181 (8.9-fold) combinations enriched. These findings provide valuable insights into the genomic features of multi-carbapenemase Enterobacterales to support the development of effective surveillance programmes.

microbiology↗

Benchmarking strain-level profiling of Escherichia coli in short-read gut metagenomes

2.Metagenomes offer the potential to characterise Escherichia coli strain-level diversity within the human gut microbiome, informing our understanding of colonisation diversity and the genetic features distinguishing infection from carriage. Among numerous reference-based tools for short-read metagenomic strain-level profiling, the best approach remains unclear. Here, we benchmarked six published tools--PanTax, PathoScope, StrainGE, Strainify, StrainR2 and StrainScan--for their ability to detect co-existing strains of E. coli and estimate their relative abundance across real and simulated metagenomes of increasing complexity with varying reference database composition. In the ZymoBIOMICS(R) D6331 dataset, only PanTax achieved zero error when predicting the equal abundance of five E. coli strains. In a differentially abundant four-strain mock community dataset (SRR13355226), StrainScan had the lowest mean absolute proportional error (0.89), driven by reduced sensitivity (0.5), followed by PathoScope (4.08). Across simulated metagenomes reflecting the healthy adult gut microbiome, all tools demonstrated high sensitivity ([≥]0.833), but specificity, precision and F1 score were selectively improved in some tools through detection thresholds to remove low abundance false positives. Outright, StrainGE achieved the highest F1 score (0.978). Predicted relative abundances of the E. coli K12-MG1655 (phylogroup A) and O157:H7 Sakai (phylogroup E) strains spiked into simulated metagenomes across varying abundance ratios were generally accurate, with PanTax and StrainR2 showing the lowest mean absolute proportional error (0.06). When truly present strains were removed from the reference database, out-of-phylogroup assignments were observed for some tools. Collectively, our results demonstrate that published metagenomic strain-level profiling tools vary in their ability to profile E. coli strains, indicating that method selection should be guided by intended application. These findings will facilitate characterisation of E. coli strain-level diversity within short-read gut metagenomes with greater accuracy than previously possible. 3. Impact statementStrain-level diversity within the human gut microbiome can be important for human health, with species such as Escherichia coli existing as both commensal and pathogenic strains. Most existing gut microbiome datasets are from short-read i.e., Illumina, sequencing, and numerous bioinformatic tools have been developed to profile strain-level variation from these data. However, the existing literature is often difficult to navigate given that the available tools have been benchmarked in various ways and are subject to author bias. This is, to our knowledge, the first independent benchmarking of six published tools for profiling E. coli at strain-level resolution from short-read metagenomes. Using both real and simulated datasets of increasing complexity, we demonstrate substantial variation in tool performance in terms of strain detection and relative abundance estimation, highlighting that tool choice should be guided by the specific research question, as no single method performs optimally across all scenarios. This work provides an unbiased framework for tool selection and will support more accurate and reproducible E. coli strain-level analyses in gut microbiome research from short-metagenomic data. 4. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Supplementary methods, six supplementary tables and four supplementary figures are available in the online Supplementary Material. Code for simulating metagenomes using InSilicoSeq, SLURM job scripts for the simulated metagenomes dataset and R visualization and statistical analysis scripts are available within a dedicated public GitHub repository (https://github.com/mattgal11/benchmarking_short_read_strain_profilers). The following supplementary data are available on FigShare (https://doi.org/10.6084/m9.figshare.32125474): O_LINormalised per-contig relative abundances for 98 species assemblies used to construct the baseline gut microbiome profile for InSilicoSeq metagenome simulation (Normalised_relative_abundance_for_InSilicoSeq_simulated_metagenomes_ gut_microbiome_profile.csv) C_LIO_LIZymoBIOMICS(R) D6331 gut microbiome standard dataset predicted relative abundance data (Zymobiomics_D6331_raw_predicted_abundance.csv) C_LIO_LISRR13355226 mock community (99% human reads; 1% E. coli reads) paired-end reads with human reads depleted (SRR13355226_depleted_R1.fastq.gz & SRR13355226_depleted_R2.fastq.gz) C_LIO_LISRR13355226 mock community dataset raw predicted abundance data, with and without human read removal (SRR13355226_raw_predicted_abundance_with_and_without_human_read_r emoval.csv) C_LIO_LISimulated metagenomes dataset raw call types and detection metric values with increasing detection thresholds (Simulated_metagenomes_raw_call_type_assingments_and_detection_thres holds.csv) C_LIO_LISimulated metagenomes dataset (all references) predicted relative abundance data (Simulated_metagenomes_all_references_raw_predicted_abundances.csv) C_LIO_LISimulated metagenomes dataset (all references) mapped reads for PathoScope and Strainify (all_refs_pathoscope_reads_mapped.csv & all_refs_strainify_reads_mapped.csv) C_LIO_LISimulated metagenomes dataset (reduced reference database) predicted relative abundance data (Simulated_metagenomes_K12_and_Sakai_removed_from_reference_datab ase_raw_predicted_abundance.csv) C_LI

bioinformatics↗

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↗

Nanopore long-read only genome assembly of clinical Enterobacterales isolates is complete and accurate

Whole bacterial genome sequence reconstruction using Oxford Nanopore Technologies ("Nanopore") long-read only sequencing may offer a lower-cost, higher-throughput alternative for pathogen surveillance to hybrid assembly with recent improvements in Nanopore sequencing accuracy. We evaluated the accuracy, including plasmid reconstruction, of Nanopore long-read only genome assemblies of Enterobacterales. We sequenced 92 genomes from clinical Enterobacterales isolates, collected in England under a national surveillance program, with long-read Nanopore (R10.4.1, Dorado v5.0.0 super-high-accuracy basecalled) and short-read Illumina (NovaSeq) sequencing approaches. Genomes were assembled using three long-read only (Flye; Hybracter long; Autocycler), and three hybrid assemblers (Hybracter hybrid; Unicycler normal; bold). Three polishing modalities (Medaka v2 with subsampled or un-subsampled long-reads; Polypolish + Pypolca with short-reads) were investigated. Autocycler circularised the most chromosomes (87/92 [95%]). Plasmid sequence reconstruction was comparable between all assemblers except Flye, all recovering 90-96% of plasmids, although the ground truth was uncertain. Flye performed worse than other assemblers on almost all metrics. Autocycler + Medaka (un-subsampled long-reads) was the most accurate long-read only assembler/polisher combination, comparable to hybrid assemblies (median 0 [IQR:0-0] SNPs and 0 [IQR:0-1] indels per genome; quality value/Q score, 100 [IQR: 64-100]), with only 4/92 genome sequences having >10 SNPs/indels. Medaka polishing with un-subsampled long-reads resulted in small improvements in indels but not SNPs for both Flye and Autocycler assemblies. Seven-locus MLST, antimicrobial resistance, virulence, and stress gene annotation was equivalent across assembler/polisher combinations. Nanopore long-read only bacterial genome assembly with Autocycler combined with Medaka polishing (using un-subsampled reads) is similarly accurate and possibly more complete than hybrid assemblies, representing a viable alternative for incorporating high-quality genomic data, including plasmids, into Enterobacterales surveillance. Data SummaryNanopore long-reads and Illumina short-reads from the 92 Enterobacterales isolates from this study have been uploaded to ENA (BioProject accession: PRJEB93885). Code for the Nextflow assembly pipeline, downstream analysis scripts, and R statistical analysis scripts are available on GitHub (https://github.com/oxfordmmm/NEKSUS_ont_hybrid_assembly_comparison). The following supplementary data tables are available on FigShare (https://figshare.com/account/home#/projects/253775): O_LIENA Sample accessions and sample metadata (accessions_and_metadata.csv) C_LIO_LISeqkit stats summaries of the Illumina and Nanopore reads (raw_qc_sup.cav) C_LIO_LISummary of assembly contig features (contigs_summary_sup_cleaned.csv) C_LIO_LIPairwise mash distances between contigs (mash_cleaned.csv) C_LIO_LIPlasmids matching across different assemblers compared to the Hybracter (hybrid) and manually-curated reference sets (plasmids_match_hybracter_mash.csv; plasmids_match_manual_mash.csv, respectively) C_LIO_LISeven-locus multi-locus sequence type annotation (mlst_cleaned.csv) C_LIO_LICheckM2 summaries of assemblies (checkm2_cleaned.csv) C_LIO_LINucleotide-level accuracy of assemblies (SNP, Indels, and Quality value compared to short-read mapping; assembly_nucleotide_accuracy_cleaned.csv) C_LIO_LIBakta annotation (bakta_by_contig_cleaned.csv) C_LIO_LIAMRFinderPlus annotations of contigs (amrfinder_plus_cleaned.csv) C_LIO_LIMOB-suite annotation summaries of contigs (mobsuite_cleaned.csv) C_LI Impact StatementNanopore long-reads have historically been too error-prone to use alone for accurate bacterial genome assembly, necessitating additional Illumina short-reads to achieve structurally complete and accurate hybrid genome assemblies for public health surveillance. This increases cost and complexity. Previous studies have shown that recent improvements in Nanopore chemistry (R10.4.1 flowcell) and basecalling (super-high accuracy) allow high-quality long-read only assemblies on a small number of laboratory reference strains. This is the first evaluation, to our knowledge, to assess Nanopore long-read only genome assembly compared with hybrid assembly on a large number of clinical isolates. In addition, this is the first large-scale evaluation of the recently released automated consensus long-read assembly tool, Autocycler. We show that Autocycler long-read only assemblies are more structurally complete for chromosomal sequences, while reconstructing a similar number of plasmids to other long-read and hybrid assemblers. Most long-read polished, Autocycler-assembled genome sequences have 0 errors (median: 0 SNPs/indels) relative to a short-read polished (hybrid) Autocycler assemblies, enabling accurate annotation of key genes.

bioinformatics↗

E. coli phylogeny drives co-amoxiclav resistance through variable expression of blaTEM-1

Co-amoxiclav resistance in E. coli is a clinically important phenotype associated with increased mortality. The class A beta-lactamase blaTEM-1 is often carried by co- amoxiclav-resistant pathogens, but exhibits high phenotypic heterogeneity, making genotype-phenotype predictions challenging. We present a curated dataset of n=377 E. coli isolates representing all 8 known phylogroups, where the only acquired beta- lactamase is blaTEM-1. For all isolates, we generate hybrid assemblies and co-amoxiclav MICs, and for a subset (n=67/377), blaTEM-1 qPCR expression data. First, we test whether certain E. coli lineages are intrinsically better or worse at expressing blaTEM-1, for example, due to lineage differences in regulatory systems, which are challenging to directly quantify. Using genotypic features of the isolates (blaTEM-1 promoter variants and copy number), we develop a hierarchical Bayesian model for blaTEM-1 expression that controls for phylogeny. We establish that blaTEM-1 expression intrinsically varies across the phylogeny, with some lineages (e.g. phylogroups B1 and C, ST12) better at expression than others (e.g. phylogroups E and F, ST372). Next, we test whether phylogenetic variation in expression influences the resistance of the isolates. With a second model, we use genotypic features (blaTEM-1 promoter variants, copy number, duplications; ampC promoter variants; efflux pump AcrF presence) to predict isolate MIC, again controlling for phylogeny. Lastly, we use a third model to demonstrate that the phylogenetic influence on blaTEM-1 expression causally drives the variation in co- amoxiclav MIC. This underscores the importance of incorporating phylogeny into genotype-phenotype predictions, and the study of resistance more generally.

microbiology↗

Global genomic epidemiology of blaGES-5 carbapenemase-associated integrons

Antimicrobial resistance (AMR) gene cassettes comprise an AMR gene flanked by short recombination sites (attI x attC or attC x attC). Integrons are genetic elements able to capture, excise, and shuffle these cassettes, providing adaptation on demand, and can be found on both chromosomes and plasmids. Understanding the patterns of integron diversity may help to understand the epidemiology of AMR genes. As a case study, we examined the clinical resistance gene blaGES-5, an integron-associated class A carbapenemase first reported in Greece in 2004 and since observed worldwide, which to our knowledge has not been the subject of a previous global analysis. Using a dataset comprising all NCBI contigs containing blaGES-5 (n = 431), we developed a pangenome graph-based workflow to characterise and cluster the diversity of blaGES-5 -associated integrons. We demonstrate that blaGES-5-associated integrons on plasmids are different to those on chromosomes. Chromosomal integrons were almost all identified in P. aeruginosa ST235, with a consistent gene cassette content and order. We observed instances where insertion sequence IS110 disrupted attC sites, which might immobilise the gene cassettes and explain the conserved integron structure despite the presence of intI1 integrase promoters, which would typically facilitate capture or excision and rearrangement. The plasmid-associated integrons were more diverse in their gene cassette content and order, which could be an indication of greater integrase activity and shuffling of integrons on plasmids.

genomics↗

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↗

Evaluation of the accuracy of bacterial genome reconstruction with Oxford Nanopore R10.4.1 long-read-only sequencing

2.Whole genome reconstruction of bacterial pathogens has become an import tool for tracking antimicrobial resistance spread, however accurate and complete assemblies have only been achievable using hybrid long and short-read sequencing. We have previously found the Oxford Nanopore Technologies (ONT) R10.4/kit12 flowcells produced improved assemblies over the R9.4.1/kit10, however they contained too many errors compared to hybrid Illumina-ONT assemblies. ONT have since released the R10.4.1/kit12 flowcells that promises greater accuracy and yield. They have also released newly trained basecallers using native bacterial DNA containing methylation sites intended to fix systematic errors, specifically Adenosine (A) to Guanine (G) and Cytosine (C) to Thymine (T) substitutions. ONT have recommended the use of Bovine Serum Albumin (BSA) during library preparation to improve sequencing yield and accuracy. To evaluate these improvements, we sequenced DNA extracts from four commonly studied bacterial pathogens, namely Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus, as well as 12 disparate E. coli clinical samples from different phylogroups and sequence types. These were all sequenced with and without BSA. These sequences were de novo assembled and compared against Illumina-corrected reference genomes. Here we have found the nanopore long read-only R10.4.1 (kit14) assemblies with basecallers trained using native bacterial methylated DNA produce accurate assemblies from 40x depth or higher, sufficient to be cost-effective compared to hybrid long-read (ONT) and short-read (Illumina) sequencing. 3. Impact statementCurrently, the best method of building accurate and complete bacterial genome assemblies is to create a hybrid assembly; combining both long and short DNA sequencing reads. Short reads are more accurate, but can be difficult to assemble into a complete genome. Long reads are generally less accurate, but easier to reconstruct into a complete genome. By combining long and short reads, we get both accuracy and reconstructive power. However, this also involves higher costs and more labour than using a single sequencing platform. In this study, we compare long read only assemblies from Oxford Nanopore Technologys newest iteration of improvements in both chemistry and software to hybrid Illumina-Nanopore assemblies. We sequenced four bacterial pathogens with published reference genomes (Staphylococcus aureus, Klebsiella Pneumoniae, Pseudomonas Aeruginosa, and Escherichia Coli) and twelve bloodstream associated E. coli, and show that assemblies from the newest technology are not only an improvement on the previous iteration, but are able to compete with hybrid Illumina-Nanopore assemblies in their quality, providing a step towards bacterial genome assembly using a single sequencing platform. 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 and Illumina fastq data are available in the ENA under project accession: PRJEB51164. Assemblies have been made available at: https://figshare.com/articles/dataset/R10_4_1_KIT14_comparison_assemblies/2497 2954 Code and analysis outputs are available at: https://gitlab.com/ModernisingMedicalMicrobiology/assembly_comparison

microbiology↗

A workflow for the detection of antibiotic residues, measurement of water chemistry and preservation of hospital sink drain samples for metagenomic sequencing

Structured summaryO_ST_ABSBackgroundC_ST_ABSHospital sinks are environmental reservoirs that harbour healthcare-associated (HCA) pathogens. Selective pressures in sink environments, such as antibiotic residues, nutrient waste and hardness ions, may promote antibiotic resistance gene (ARG) exchange between bacteria. However, cheap and accurate sampling methods to characterise these factors are lacking. AimTo validate a workflow to detect antibiotic residues and evaluate water chemistry using dipsticks. Secondarily, to validate boric acid to preserve the taxonomic and ARG ("resistome") composition of sink trap samples for metagenomic sequencing. MethodsAntibiotic residue dipsticks were validated against serial dilutions of ampicillin, doxycycline, sulfamethoxazole and ciprofloxacin, and water chemistry dipsticks against serial dilutions of chemical calibration standards. Sink trap aspirates were used for a "real-world" pilot evaluation of dipsticks. To assess boric acid as a preservative of microbial diversity, the impact of incubation with and without boric acid at [~]22{degrees}C on metagenomic sequencing outputs was evaluated at Day 2 and Day 5 compared with baseline (Day 0). FindingsThe limits of detection for each antibiotic were: 3{micro}g/L (ampicillin), 10{micro}g/L (doxycycline), 20{micro}g/L (sulfamethoxazole) and 8{micro}g/L (ciprofloxacin). The best performing water chemistry dipstick correctly characterised 34/40 (85%) standards in a concentration-dependent manner. One trap sample tested positive for the presence of tetracyclines and sulfonamides. Taxonomic and resistome composition were largely maintained after storage with boric acid at [~]22{degrees}C for up to five days. ConclusionsDipsticks can be used to detect antibiotic residues and characterise water chemistry in sink trap samples. Boric acid was an effective preservative of trap sample composition, representing a low-cost alternative to cold-chain transport.

microbiology↗

Identification of a novel MCR-1 variant displaying low level of co-resistance to β-lactam antibiotics that uncovers a potential novel antimicrobial peptide

The emerging and global spread of a novel plasmid-mediated colistin resistance gene, mcr-1, threatens human health. It is accepted that MCR-1 affects bacterial fitness, and this fitness cost correlates with bacterial membrane lipid A perturbation. However, the detailed molecular mechanism remains unclear. Here, we screened out a novel MCR-1 variant, named M6, with a two-point mutation that rendered a low level of co-resistance to {beta}-lactam antibiotics. Compared to wild-type (WT) MCR-1, this variant caused severe lipid A perturbation resulting in peptidoglycan layer remodelling and thus resulted in phenotypic co-resistance to {beta}-lactams. Moreover, we found that a lipid A loading cavity is localized at the linker domain of MCR-1 and governs colistin resistance and bacterial membrane permeability, and the mutated pocket of M6 facilitates the binding affinity of lipid A. More importantly, synthetic peptides derived from M6 achieved broad-spectrum antimicrobial activity. These findings provide insights into a potential vulnerability that could be exploited in future antimicrobial drug design.

microbiology↗

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↗

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↗

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↗

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↗

Discordance between different bioinformatic methods for identifying resistance genes from short-read genomic data, with a focus on Escherichia coli

2.Several bioinformatics genotyping algorithms are now commonly used to characterise antimicrobial resistance (AMR) gene profiles in whole genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly Escherichia coli, is of major importance, because this is a common pathogen. However, robust comparisons of different genotyping approaches on relevant simulated and large real-life WGS datasets are lacking. Here, we used both simulated datasets and a large set of real E. coli WGS data (n=1818 isolates) to systematically investigate genotyping methods in greater detail. Simulated constructs and real sequences were processed using four different bioinformatic programs (ABRicate, ARIBA, KmerResistance, and SRST2, run with the ResFinder database) and their outputs compared. For simulations tests where 3,079 AMR gene variants were inserted into random sequence constructs, KmerResistance was correct for 3,076 (99.9%) simulations, ABRicate for 3,054 (99.2%), ARIBA for 2,783 (90.4%) and SRST2 for 2,108 (68.5%). For simulations tests where two closely related gene variants were inserted into random sequence constructs, KmerResistance the correct alleles in 35,338/46,318 (76.3%) ABRicate identified in 11,842/46,318 (25.6%) of simulations, ARIBA in 1679/46,318 (3.6%), and SRST2 in 2000/46,318 (4.3%). In real data, across all methods, 1392/1818 (76%) isolates had discrepant allele calls for at least one gene. Our evaluations revealed poor performance in scenarios that would be expected to be challenging (e.g. identification of AMR genes at <10x coverage, discriminating between closely related AMR gene sequences), but also identified systematic sequence classification (i.e. naming) errors even in straightforward circumstances, which contributed to 1081/3092 (35%) errors in our most simple simulations and at least 2530/4321 (59%) discrepancies in real data. Further, many of the remaining discrepancies were likely "artefactual" with reporting cut-off differences accounting for at least 1430/4321 (33%) discrepants. Comparing outputs generated by running multiple algorithms on the same dataset can help identify and resolve these artefacts, but ideally new and more robust genotyping algorithms are needed. 3. Impact statementWhole-genome sequencing is widely used for studying the epidemiology of antimicrobial resistance (AMR) genes in bacteria; however, there is some concern that outputs are highly dependent on the bioinformatics methods used. This work evaluates these concerns in detail by comparing four different, commonly used AMR gene typing methods using large simulated and real datasets. The results highlight performance issues for most methods in at least one of several simulated and real-life scenarios. However most discrepancies between methods were due to differential labelling of the same sequences related to the assumptions made regarding the underlying structure of the reference resistance gene database used (i.e. that resistance genes can be easily classified in well-defined groups). This study represents a major advance in quantifying and evaluating the nature of discrepancies between outputs of different AMR typing algorithms, with relevance for historic and future work using these algorithms. Some of the discrepancies can be resolved by choosing methods with fewer assumptions about the reference AMR gene database and manually resolving outputs generated using multiple programs. However, ideally new and better methods are needed.

microbiology↗

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↗

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↗

Genomic network analysis of an environmental and livestock IncF plasmid population

IncF plasmids are diverse and of great clinical significance, often carrying genes conferring antimicrobial resistance (AMR) such as extended-spectrum {beta}-lactamases, particularly in Enterobacteriaceae. Organising this plasmid diversity is challenging, and current knowledge is largely based on plasmids from clinical settings. Here, we present a network community analysis of a large survey of IncF plasmids from environmental (influent, effluent, and upstream/downstream waterways surrounding wastewater treatment works) and livestock settings. We use a tractable and scalable methodology to examine the relationship between plasmid metadata and network communities. This reveals how niche (sampling compartment and host genera) partition and shape plasmid diversity. We also perform pangenome-style analyses on network communities. We show that such communities define unique combinations of core genes, with limited overlap. Building plasmid phylogenies based on alignments of these core genes, we demonstrate that plasmid accessory function is closely linked to core gene content. Taken together, our results suggest that stable IncF plasmid backbone structures can persist in environmental settings while allowing dramatic variation in accessory gene content that may be linked to niche adaptation. The recent association of IncF plasmids with AMR likely reflects their suitability for rapid niche adaptation.

bioinformatics↗