Biology subjects

Wick, R. R.

Publications and source records attributed to Wick, R. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Evaluating Nanopore read trimming and quality filtering in bacterial genomics

Oxford Nanopore Technologies (ONT) sequencing is widely used in bacterial genomics, particularly for reference-based variant calling and de novo assembly. Both analyses routinely start with quality control (QC) preprocessing, but as ONT basecalling accuracy has improved, its necessity and downstream trade-offs remain poorly defined. We benchmarked 17 preprocessing combinations, built from three adapter trimmers (Dorado, Porechop_ABI, Barbell) and three quality-based processing tools (Filtlong, Chopper, SeqKit) with untrimmed and unprocessed controls, plus Fastplong, which performs both. Each combination was evaluated across 13 bacterial isolates at 100x and 20x depth under the HAC and SUP basecalling models. Variant calling was assessed by F1 score. Assemblies were scored on sequence accuracy, contiguity, replicon recovery and residual adapter contamination, then aggregated into a weighted arithmetic mean using weights from a survey of the microbial genomics community. With SUP basecalling, raw reads with no trimming or quality-based processing produced accurate SNP calls and outperformed several pipelines that applied both operations; adapter trimming alone left SNP accuracy unchanged. Subsetting reads by combined length and quality with Filtlong gave the highest SNP F1 scores at both depths, except with Barbell at 20x, where it ranked second lowest. As is often the case in benchmarking studies, assembly results involved trade-offs, and the best tool depends on which aspects of performance matter most for a given use. Filtlong produced the lowest error rates, but every Filtlong pipeline lost three small plasmids at both depths. Barbell trimming raised error rates and reduced contiguity at 20x, while skipping adapter trimming left residual adapter and barcode sequences in assemblies. Under the community-derived weights, Porechop_ABI followed by Chopper had the highest overall score at both depths, without winning any single metric. QC tool choice should therefore be guided by the downstream analysis goal rather than applied indiscriminately across all workflows.

bioinformatics↗

bioRxiv2026

Bacterial diversity and strain dynamics in the infant respiratory microbiome during the first year of life

BackgroundMicrobial colonisation of the human body begins immediately after birth, with each body site forming a distinct ecological niche. While early gut microbial dynamics and their links to paediatric health have been considerably studied, the bacterial colonisation of the early infant respiratory system remains poorly understood, particularly at the species and strain level. ResultsHere, we generated and analysed whole genome sequencing of 925 isolates from six dominant genera in nasopharyngeal samples from 58 healthy infants enrolled in the Childhood Asthma Study (CAS) in Western Australia, collected longitudinally from birth (2, 6, and 12 months old). Our results expanded genomic reference catalogues and uncovered substantial strain-level diversity in dominant infant airway taxa. Plate-sweep metagenomics identified four microbiome profile groups (MPGs) with age-dependent membership, confirming prior observations while enabling high-resolution species and strain analyses. Community maturation was characterised by a shift from early Staphylococcus aureus dominance to increased Moraxella catarrhalis dominance by 12 months of age, alongside marked temporal changes in prevalence and cohort-level strain diversity. ConclusionsThese findings resolve infant nasopharyngeal microbiota composition at the species and strain level, revealing taxon-specific colonisation patterns. By substantially expanding publicly available reference genomes for underrepresented airway taxa, this work also provides a foundation for functional follow-up studies of the early respiratory microbiota and respiratory outcomes.

microbiology↗

bioRxiv2026

Benchmarking long-read simulators against Oxford Nanopore whole-genome sequencing data

BackgroundOxford Nanopore Technologies (ONT) sequencing is increasingly used for whole-genome sequencing (WGS) across a wide range of applications. However, the platform has evolved rapidly through updates to flow cell chemistry and basecalling algorithms, altering the characteristics of the resulting sequencing data. Read simulators provide synthetic datasets with known ground truth, enabling controlled development and evaluation of methods. However, many existing simulators were developed for earlier versions of ONT sequencing or use generic long-read assumptions, and their realism for contemporary ONT data is unclear. ResultsWe benchmarked six ONT-compatible read simulators (Badread, LongISLND, lrsim, NanoSim, PBSIM3 and SimLoRD) using a microbial genome reference and ONT R10.4.1 reads as the empirical standard. Each tool was configured to maximise realism, including training on empirical reads when supported. We compared simulated and real datasets with respect to read length, read accuracy, FASTQ quality scores and sequence error profiles. No simulator reproduced all metrics of the real data well. PBSIM3 most closely reproduced read length, read accuracy and FASTQ quality scores, making it a strong simulator for broad read-level realism. However, it did not capture important features of the real error profile, including context-dependent substitution rates and homopolymer-length errors. Badread and LongISLND better reproduced some aspects of the error profile, but showed other departures from the real data. ConclusionPBSIM3 is a good general-purpose choice for many ONT WGS simulation tasks because it reproduced several key read-level properties well. However, Badread or LongISLND may be preferable for applications where error structure is more important. No evaluated tool was realistic across all tested metrics, highlighting a gap for improved long-read simulators.

bioinformatics↗

bioRxiv2026

Verticall: A fast and robust tool for recombination detection in large-scale bacterial genomic datasets

The inference and removal of horizontally acquired genomic regions is a crucial step in phylogenomics analyses for evolutionary studies. Existing tools perform well on clonal lineage-focused datasets on the scale of hundreds of genomes, but are limited in their ability to analyse larger or more diverse datasets. Here we present Verticall, a tool to identify recombinant regions in bacterial assemblies and generate recombination-free phylogenies, which scales to thousands of genomes from clonal to genus-level diversity. Verticall uses a non-parametric approach to assign genomic regions as horizontally or vertically related based on the distribution of pairwise genetic distances between genomes. Recombination-free phylogenetic trees may be inferred by either calculating a pairwise genetic distance matrix from vertical-only regions (distance-tree approach) or by pairwise comparisons of all genomes to a reference and then masking horizontally acquired regions in a pseudo-alignment to the reference (alignment-tree approach). We demonstrate Verticalls performance using four publicly available whole-genome sequence datasets of varying sample sizes (range: 154 - 4,857 genomes) and evolutionary scales (ranging from within-lineage to genus-wide diversity). Across all four datasets, Verticall showed comparable or superior performance to the established tools Gubbins and ClonalFrameML in terms of computational efficiency, plausibility of inferred phylogenetic trees, and recovery of temporal signal for molecular dating. Our results show that Verticall is a useful tool to more efficiently and accurately detect recombination, particularly applied to datasets for which existing tools are limited, including large datasets with hundreds to thousands of genomes and those that span entire species or genera. Verticall is available free and open source at https://github.com/rrwick/Verticall. Impact StatementMany bacterial species can acquire genetic material from external sources and stably incorporate them into their own genomes through homologous recombination. During phylogenomic analyses to investigate outbreaks or for evolutionary studies, a core objective is often to reconstruct the evolutionary history of the studied organisms independent of these horizontally acquired genomic regions. This is particularly desirable when the aim is to construct dated phylogenies, as horizontally acquired variation can interfere with the molecular clock signal on which dating relies. Existing recombination detection programs perform well in certain contexts, but their algorithms are not suitable for datasets with very high diversity or thousands of genomes. We addressed this gap by developing the software package Verticall. We show this approach produces comparable results to existing software for smaller more clonal datasets, but also performs well on datasets that the existing packages cannot handle. Data SummaryVerticall is available free and open source at https://github.com/rrwick/Verticall. We used published whole-genome sequence data deposited in public databases (Pathogenwatch [https://pathogen.watch/]; European Nucleotide Archive [https://www.ebi.ac.uk/ena/], Sequence Read Archive [https://www.ncbi.nlm.nih.gov/sra/]). Accession numbers for the raw whole-genome sequences are presented in Tables S2-S6. All data, code, and analysis commands used to generate the results and figures presented in this paper are available on figshare (DOI: 10.6084/m9.figshare.31930821) and GitHub (https://github.com/erkison/verticall_paper).

bioinformatics↗

bioRxiv2026

Flex-It: A global standardised genotyping framework for Shigella flexneri

Shigella flexneri is the leading causative agent of shigellosis globally. The public health threat posed by S. flexneri is compounded by its emergence as a sexually transmissible infection, importance of international travel in driving dissemination, and the increasing prevalence of antimicrobial resistance (AMR). A rapid and robust computational method is needed to enhance genomic surveillance and systematically explore features of the population structure of this WHO priority pathogen, which is scalable and readily implementable across jurisdictions, particularly as vaccine development efforts are underway. Here, we present Flex-It, a genomic framework and genotyping scheme implemented in Mykrobe for S. flexneri serotypes 1-5, X & Y, compatible with previous approaches used to describe S. flexneris population structure. To develop Flex-It, we curated a retrospective dataset of 5,819 publicly available S. flexneri genomes. We characterised the global population structure for S. flexneri, exploring geographical and temporal traits, and showed the granular diversity of AMR and serotype profiles. We applied Flex-It to >13,000 genomes routinely generated by public health laboratories from Australia, the UK and the USA across a ten-year period. We found significant genotype diversity in all three locations, with the emergence of genotypes with converged resistance to all major drugs currently used for treatment. Flex-It provides an open-source, novel genotyping method that rapidly characterises S. flexneri and its ciprofloxacin resistance determinants in <1 minute from both short and long whole-genome sequencing reads. Flex-It provides the community with a standardised nomenclature to monitor the emergence and spread of S. flexneri lineages.

microbiology↗

bioRxiv2025

agtools: a software framework to manipulate assembly graphs

SummaryAssembly graphs are a fundamental data structure used by genome and metagenome assemblers to represent sequences and their overlap information, facilitating the assembler to construct longer genomic fragments. Apart from their core use in assemblers, assembly graphs have become increasingly important in a range of downstream applications such as metagenomic binning, plasmid detection, viral genome resolution and haplotype phasing. However, there is a need for a comprehensive tool that allows programmatic access to manipulate assembly graphs across different assembly graph formats. Here we present agtools, an open-source Python framework that can analyse and manipulate assembly graphs. agtools provides a command-line interface for tasks such as graph format conversion, segment filtering, and component extraction. It also exposes a Python package interface to load, query and analyse assembly graphs from popular genome and metagenome assemblers. This enables streamlined assembly graph-based analysis that can be integrated into other bioinformatics software and workflows. Availability and implementationThe source code of agtools is hosted on GitHub at https://github.com/Vini2/agtools and the documentation is available at https://agtools.readthedocs.io/. agtools is also installable from Bioconda (https://anaconda.org/bioconda/agtools) and PyPI (https://pypi.org/project/agtools/).

bioinformatics↗

bioRxiv2025

Benchmarking of tools for resolving plasmids from short-read assemblies for Klebsiella pneumoniae

Plasmids play a critical role in the dissemination of antimicrobial resistance genes and virulence factors in healthcare associated pathogens, such as Klebsiella pneumoniae. Surveillance of these plasmids relies on whole genome sequencing data often generated in clinical and public health settings which frequently use short-read platforms. Therefore, there is a need for robust, scalable tools that can identify and/or reconstruct plasmid sequences from short read data. A myriad of tools already exist to address this problem, however the optimum tool for plasmid identification in K. pneumoniae remains unclear. From a comprehensive search of the literature and code repositories we identified 44 plasmid identification tools, highlighting the uncertainty around best practices. Here, we sought to evaluate these 44 tools to determine which is best suited for reconstructing the plasmidome of K. pneumoniae and related species from the species complex (KpSC). We used a publicly available dataset of 568 diverse KpSC isolates that had both short-read Illumina data and closed hybrid assemblies available. This allowed us to investigate which tools perform best at recovering plasmid sequences when only short-read data is available, whilst knowing the ground truth. From the 44 tools, 34 were excluded as they: were intended for plasmid typing / characterisation (n=3), were not intended for KpSC (n=1), required metagenomic data (n=7), required long read data (n=1), could not be installed (n=13) or could not be run on the command line (n=10). The remaining nine tools had their precision and recall metrics calculated and combined into an overall F1 score. Each individual tool displayed the full range of F1 scores (0 to 1) across our collection of genomes, overall, the best performing was PlaScope followed closely by MOB-suite. Future tools developed in this crowded space should offer meaningful advancements over existing tools and be rigorously benchmarked using standardised datasets that reflect plasmid diversity.

genomics↗

bioRxiv2025

Novel insights into the genome organization of Rhizobiaceae: identification of linear plasmids

2.Members of the family Rhizobiaceae typically have multipartite genomes, that are split between two or more replicons, including the chromosome and a variable number of extrachromosomal replicons (chromids and plasmids). Nearly all Rhizobiaceae replicons sequenced and described to date have a circular topology, with the exception of the linear chromid found in the genomes of most Agrobacterium spp. In this study, genomes of five nonpathogenic Agrobacterium strains and one plant tumorigenic Allorhizobium strain were fully sequenced. Surprisingly, genome analysis revealed that these six strains each carry an 80-kbp linear plasmid. Linear plasmids were so far not identified in this bacterial family or other bacteria within the class Alphaproteobacteria. The ends of all six plasmids identified in this study have a hairpin structure with covalently closed ends. The plasmid sequences showed a high degree of homology, clearly indicating their common ancestry. Database searches led to the identification of additional linear plasmids in previously published Rhizobiaceae genome assemblies that were not previously recognized to have linear plasmids, suggesting that these replicons may be more widespread. Most likely, linear plasmids may be even more widely distributed than anticipated. Although the biological functions of the linear plasmids identified in this study remain unknown, they are associated with both nonpathogenic and plant tumorigenic Rhizobiaceae strains. 3. Impact statementThe family Rhizobiaceae includes some remarkable and important representatives, such as plant symbiotic bacteria (rhizobia) and plant pathogenic bacteria associated with neoplasia (agrobacteria). In this study, the complete genome sequences of six Rhizobiaceae strains were generated and their genome organizations were examined. Strikingly, our results showed that these six strains harbor a linear plasmid. Moreover, GenBank searches suggested that linear plasmids may be even more widespread in the family Rhizobiaceae. Linear plasmids may go undetected in genome sequencing studies if the assemblies are not specifically examined for linear plasmid. Overall, this study provides further evidence for the extraordinary genome plasticity of members of the family Rhizobiaceae and expands the taxonomic range in which linear plasmids have been identified. To the best of our knowledge, this is the first report of linear plasmids in the family Rhizobiaceae or the class Alphaproteobacteria. 4. Data summaryThe whole-genome sequences have been deposited at DDBJ/ENA/GenBank under the accessions CP192696-CP192701 (Av2), CP000000-CP000000 (rho-7.1), CP000000-CP000000 (rho-8.1), CP000000-CP000000 (rho-11.1), CP000000-CP000000 (rho-13.3), and CP000000-CP000000 (rho-14.1), within the BioProjects PRJNA557463 and PRJNA1009994. The raw sequencing reads were deposited in the Sequence Read Archive (SRA) under the same BioProjects PRJNA557463 and PRJNA1009994: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA557463 and https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1009994. NCBI submission for five genome sequences is undergoing processing and accession numbers will be added when available; in https://figshare.com/s/29a9e621adc1b66d0957

genomics↗

bioRxiv2025

Amira: gene-space de Bruijn graphs to improve the detection of AMR genes from bacterial long reads

Accurate detection of antimicrobial resistance (AMR) genes is essential for the surveillance, epidemiology and genotypic prediction of AMR. This is typically done by generating an assembly from the sequencing reads of a bacterial isolate and running AMR gene detection tools on the assembly. However, despite advances in long-read sequencing that have greatly improved the quality and completeness of bacterial genome assemblies, assembly tools remain prone to large-scale errors caused by repeats in the genome, leading to inaccurate detection of AMR gene content and consequent impact on resistance prediction. In this work we present Amira, a tool to detect AMR genes directly from unassembled long-read sequencing data. Amira leverages the fact that multiple consecutive genes lie within a single read to construct gene-space de Bruijn graphs where the k-mer alphabet is the set of genes in the pan-genome of the species under study. Through this approach, the reads corresponding to different copies of AMR genes can be effectively separated based on the genomic context of the AMR genes, and used to infer the nucleotide sequence of each copy. Amira achieves significant improvements in genomic copy number recall and nucleotide accuracy, demonstrated through objective simulations and comparison with alternative read and assembly-based methods on samples with manually curated truth assemblies. Applied to a dataset of 32 Escherichia coli samples with diverse AMR gene content, Amira achieves a mean genomic-copy-number recall of 98.4% with precision 97.9% and nucleotide accuracy 99.9%. Finally, we show that Amira consistently detects more true AMR genes across all E. coli, K. pneumoniae and E. faecium nanopore datasets from the ENA (n=8580, 2448 and 415 respectively) than an assembly-based approach.

bioinformatics↗

bioRxiv2025

Autocycler: long-read consensus assembly for bacterial genomes

MotivationLong-read sequencing enables complete bacterial genome assemblies, but individual assemblers are imperfect and often produce sequence-level and structural errors. Consensus assembly using Trycycler can improve accuracy, but its lack of automation limits scalability. There is a need for an automated method to generate high-quality consensus bacterial genome assemblies from long-read data. ResultsWe present Autocycler, a command-line tool for generating accurate bacterial genome assemblies by combining multiple alternative long-read assemblies of the same genome. Without requiring user input, Autocycler builds a compacted De Bruijn graph from the input assemblies, clusters and filters contigs, trims overlaps and resolves consensus sequences by selecting the most common variant at each locus. It also supports manual curation when desired, allowing users to refine assemblies in challenging or important cases. In our evaluation using Oxford Nanopore Technologies reads from five bacterial isolates, Autocycler outperformed individual assemblers, automated pipelines and other consensus tools, producing assemblies with lower error rates and improved structural accuracy. Availability and implementationAutocycler is implemented in Rust, open-source and freely available at github.com/rrwick/Autocycler. It runs on Linux and macOS and is extensively documented.

bioinformatics↗

bioRxiv2025

Transposon-directed insertion-site sequencing (TraDIS) analysis of Enterococcus faecium using nanopore sequencing and a WebAssembly analysis platform

Vancomycin-resistant Enterococcus faecium (VREfm) are healthcare-associated opportunistic pathogens of global significance. Genetic tools are needed to understand the molecular basis for VREfm clinically relevant phenotypes, such as persistence within the human gut or antimicrobial resistance. Here, we present a transposon-directed insertion-site sequencing (TraDIS) platform optimised for E. faecium. We engineered a transposon delivery plasmid, pIMTA(tetM), that can generate high density transposon mutant libraries, combined with Oxford Nanopore Technology amplicon sequencing to map the transposon insertion sites. We have also customised a bioinformatic analysis suite that includes a WebAssembly-powered visualisation tool called Diana, for TraDIS data exploration and analysis (https://diana.cpg.org.au/). To demonstrate performance of our platform, we assessed the impact of vancomycin exposure on a library of 48,458 unique transposon mutants. As expected, we could confirm the importance of the vanB operon for VREfm vancomycin resistance. Our end-to-end platform for running TraDIS experiments in VREfm will permit accessible, genome-scale, forward genetic screens to probe molecular mechanisms of persistence and pathogenesis. ImportanceThere are limited genetic tools specifically developed and optimized for function in Enterococcus faecium. Here, we addressed this gap through the development of a transposon-directed insertion-site sequencing (TraDIS) platform with a plasmid we engineered to specifically function in E. faecium. The application of nanopore sequencing, with a highly accessible sequence data processing and bioinformatic analysis pipeline streamlines and simplifies the methodology. These developments will allow the functional genomic analysis of important traits involved in the pathobiology of this understudied bacterium. The approach and tools we have described here are likely applicable to other Gram-positive bacteria.

microbiology↗

bioRxiv2025

Are reads required? High-precision variant calling from bacterial genome assemblies

1.Accurate nucleotide variant calling is essential in microbial genomics, particularly for outbreak tracking and phylogenetics. This study evaluates variant calls derived from genome assemblies compared to traditional read-based variant-calling methods, using seven closely related Staphylococcus aureus isolates sequenced on Illumina and Oxford Nanopore Technologies platforms. By benchmarking multiple assembly and variant-calling pipelines against a ground truth dataset, we found that read-based methods consistently achieved high accuracy. Assembly-based approaches performed well in some cases but were highly dependent on assembly quality, as errors in the assembly led to false-positive variant calls. These findings underscore the need for improved assembly techniques before the potential benefits of assembly-based variant calling - such as reduced computational requirements and simpler data management - can be realised. 2. Impact statementVariant calling is foundational to microbial genomics, yet traditional workflows rely heavily on sequencing reads, which for a typical bacterial genome can be hundreds of megabytes. In contrast, genome assemblies are far smaller - usually just a few megabytes - making them significantly easier to manage. If accurate variant calls could be made directly from assemblies, this would reduce computational demands and, in some cases, may even eliminate the need to retain raw sequencing reads. This study addresses the key question of whether variant calling from assemblies is accurate enough to replace read-based methods. Our findings show that while assembly-based variant calling can achieve high accuracy, this is only possible with error-free assemblies. Since most assemblies contain errors, assembly-based variant-calling approaches should currently be used with caution. Nevertheless, as sequencing and assembly technologies continue to advance, improved assembly accuracy may make assembly-based variant calling a viable alternative, reducing data complexity and storage demands while streamlining microbial genomic analyses. 3. Data summarySupplementary methods, data, figures and tables are available at github.com/rrwick/Are-reads-required which is also archived on Zenodo (10.5281/zenodo.14868870). Reads and assemblies are available via BioProject PRJNA1193226.

bioinformatics↗

bioRxiv2024

The complete genome sequence of the crayfish pathogen Candidatus Paracoxiella cheracis n.g. n.sp. provides insight into pathogenesis and the phylogeny of the Coxiellaceae family

The Coxiellaceae bacterial family, within the order Legionellales, is defined by a collection of poorly characterized obligate intracellular bacteria. The zoonotic pathogen and causative agent of human Q fever, Coxiella burnetii, represents the best characterized member of this family. Coxiellaceae establish replicative niches within diverse host cells and rely on their host for survival, making them challenging to isolate and cultivate within a laboratory setting. Here we describe a new genus within the Coxiellaceae family that has been previously shown to infect economically significant freshwater crayfish. Using culture-independent long-read metagenomics, we reconstructed the complete genome of this novel organism and demonstrate that the previously referred to as Candidatus Coxiella cheraxi represents a novel genus within this family, herein denoted Candidatus Paracoxiella cheracis. Interestingly, we demonstrate that Candidatus P. cheracis encodes for a complete, putatively functional Dot/Icm type 4 secretion system that likely mediates the intracellular success of this pathogen. In silico analysis defined a unique repertoire of Dot/Icm effector proteins and highlighted homologues of several important C. burnetii effectors including a homologue of CpeB that was demonstrated to be a Dot/Icm substrate in C. burnetii. IMPORTANCEUsing long-read sequencing technology we have uncovered the full genome sequence of Candidatus Paracoxiella cheracis, a pathogen of economic importance in aquaculture. Analysis of this sequence has revealed new insight into this novel member of the Coxiellaceae family, demonstrating that it represents a new genus within this poorly characterized family of intracellular organisms. Importantly, the genome sequence reveals invaluable information that will support diagnostics and potentially both preventative and treatment strategies within crayfish breeding facilities. Candidatus P. cheracis also represents a new member of Dot/Icm pathogens that rely on this system to establish an intracellular niche. Candidatus P. cheracis possesses a unique cohort of putative Dot/Icm substrates that constitute a collection of new eukaryotic cell biology manipulating effector proteins.

microbiology↗

bioRxiv2024

Typhi Mykrobe: fast and accurate lineage identification and antimicrobial resistance genotyping directly from sequence reads for the typhoid fever agent Salmonella Typhi

BackgroundTyphoid fever results from systemic infection with Salmonella enterica serovar Typhi (Typhi) and causes 10 million illnesses annually. Disease control relies on prevention (water, sanitation, and hygiene interventions or vaccination) and effective antimicrobial treatment. Antimicrobial resistant (AMR) Typhi lineages have emerged and become established in many parts of the world. Knowledge of local pathogen populations informed by genomic surveillance, including of lineages (defined by the GenoTyphi scheme) and AMR determinants, is increasingly used to inform local treatment guidelines and to inform vaccination strategy. Current tools for genotyping Typhi require multiple read alignment or assembly steps and have not been validated for analysis of data generated with Oxford Nanopore Technologies (ONT) long-read sequencing devices. Here, we introduce Typhi Mykrobe, a command line software tool for rapid genotyping of Typhi lineages, AMR determinants, and plasmid replicons direct from sequencing reads. ResultsWe validated Typhi Mykrobe lineage genotyping by comparison with the current standard read mapping-based approach and demonstrated 99.8% concordance across nearly 13,000 genomes sequenced with Illumina platforms. For the few isolates with discordant calls, we show that Typhi Mykrobe results are better supported by the evidence from raw sequence read data than the results generated using the mapping-based approach. We also demonstrate 99.9% concordance for detection of AMR determinants compared with the current standard assembly-based approach, with similar results for plasmid marker detection. Typhi Mykrobe predicts clinical resistance categorisation (S/I/R) for eight drug classes, and we show strong agreement with phenotypic categorisations generated from reference laboratory minimum inhibitory concentration (MIC) data for n=1,572 Illumina-sequenced isolates (>99% agreement within one doubling dilution). We show strong concordance (>96% for genotype and >98% for AMR and plasmid) between calls made from ONT reads and those made from Illumina reads for isolates sequenced on both platforms (n =93 genomes). Typhi Mykrobe takes less than a minute per sample and is available at https://github.com/typhoidgenomics/genotyphi. ConclusionsTyphi Mykrobe provides rapid and sensitive genotyping of Typhi genomes direct from Illumina and ONT reads, although lower accuracy was observed for R9 ONT data. It demonstrated accurate assignment of GenoTyphi lineage, detection of AMR determinants and prediction of corresponding AMR phenotypes, and identification of plasmid replicons.

microbiology↗

bioRxiv2024

A genome-wide One Health study of Klebsiella pneumoniae in Norway reveals overlapping populations but few recent transmission events across reservoirs

Members of the Klebsiella pneumoniae species complex (KpSC) are opportunistic pathogens that cause severe and difficult-to-treat infections. KpSC are common in non-human niches, but the clinical relevance of these populations is disputed. Utilising 3,255 whole-genome sequenced isolates from human, animal and marine sources collected during 2001-2020 in Norway, we showed the KpSC populations in different niches were distinct but overlapping. Notably, human infection isolates showed greatest connectivity with each other, followed by isolates from human carriage, pigs, and bivalves. Nearly 5% of human infection isolates had close relatives ([≤]22 substitutions) amongst animal and marine isolates, despite temporally and geographically distant sampling of these sources. Infection prevention measures are essential to limit transmission within human clinical settings and reduce disease burden. However, as colonisation often precedes infection, preventing transmission that leads to colonisation, e.g. transmission between animals and humans in the community, and in the food chain, could also be beneficial.

microbiology↗

bioRxiv2024

Exploring SNP Filtering Strategies: The Influence of Strict vs Soft Core

Phylogenetic analyses are crucial for understanding microbial evolution and infectious disease transmission. Bacterial phylogenies are often inferred from single nucleotide polymorphism (SNP) alignments, with SNPs as the fundamental signal within these data. SNP alignments can be reduced to a strict core by removing those sites which do not have data present in every sample. However, as sample size and genome diversity increase, a strict core can shrink markedly, discarding potentially informative data. Here, we propose and provide evidence to support the use of a soft core that tolerates some missing data, preserving more information for phylogenetic analysis. Using large datasets of Neisseria gonorrhoeae and Salmonella enterica serovar Typhi, we assess different core thresholds. Our results show that strict cores can drastically reduce informative sites compared to soft cores. In a 10,000-genome alignment of Salmonella enterica serovar Typhi, a 95% soft core yielded 10 times more informative sites than a 100% strict core. Similar patterns were observed in Neisseria gonorrhoeae. We further evaluated the accuracy of phylogenies built from strict and soft-core alignments using datasets with strong temporal signals. Soft-core alignments generally outperformed strict cores in producing trees displaying clock-like behaviour; for instance, the Neisseria gonorrhoeae 95% soft core phylogeny had a root-to-tip regression R2 of 0.50 compared to 0.21 for the strict-core phylogeny. This study suggests that soft-core strategies are preferable for large, diverse microbial datasets. To facilitate this, we developed Core-SNP-filter (github.com/rrwick/Core-SNP-filter), an open-source software tool for generating soft-core alignments from whole-genome alignments based on user-defined thresholds. IMPACT STATEMENTThis study addresses a major limitation in modern bacterial genomics - the significant data loss observed in large datasets for phylogenetic analyses, often due to strict-core SNP alignment approaches. As bacterial genome sequence datasets grow and diversity increases, a strict-core approach can greatly reduce the number of informative sites, compromising phylogenetic resolution. Our research highlights the advantages of soft-core alignment methods which tolerate some missing data and retain more genetic information. To streamline the processing of alignments, we developed Core-SNP-filter (github.com/rrwick/Core-SNP-filter), a publicly available resource-efficient tool that filters alignments to informative and core sites. DATA SUMMARYAll genomic sequence reads used in this study were already publicly available and accessions can be found in Supplementary Dataset 1. Supplementary methods and all code can be found in the accompanying GitHub repository: (github.com/mtaouk/Core-SNP-filter-methods).

genomics↗

bioRxiv2024

Targeted sequencing of Enterobacterales bacteria using CRISPR-Cas9 enrichment and Oxford Nanopore Technologies

Sequencing DNA directly from patient samples enables faster pathogen characterisation compared to traditional culture-based approaches, but often yields insufficient sequence data for effective downstream analysis. CRISPR-Cas9 enrichment is designed to improve yield of low abundance sequences but has not been thoroughly explored with Oxford Nanopore Technologies (ONT) for use in clinical bacterial epidemiology. We designed CRISPR-Cas9 guide RNAs to enrich for the human pathogen Klebsiella pneumoniae, by targeting multi-locus sequence type (MLST) and transfer RNA (tRNA) genes, as well as common antimicrobial resistance (AMR) genes and the resistance-associated integron gene intI1. We validated enrichment performance in bacterial isolates before comparing enriched and unenriched sequencing of three human faecal samples spiked with K. pneumoniae at varying abundance. Enriched sequencing generated 56x and 11.3x the number of AMR and MLST reads respectively compared to unenriched sequencing and required approximately one third of the computational storage space. Targeting the intI1 gene often led to detection of 10-20 proximal resistance genes due to the long reads produced by ONT sequencing. We demonstrated that CRISPR-Cas9 enrichment combined with ONT sequencing enabled improved genomic characterisation outcomes over unenriched sequencing of patient samples. This method could be used to inform infection control strategies by identifying patients colonised with high-risk strains.

microbiology↗

bioRxiv2024

Genomic and functional analysis of rmp locus variants in Klebsiella pneumoniae

AbstractO_ST_ABSBackgroundC_ST_ABSKlebsiella pneumoniae is an opportunistic pathogen and a leading cause of healthcare-associated infections in hospitals, which are frequently antimicrobial resistant (AMR). Exacerbating the public health threat posed by K. pneumoniae, some strains also harbor additional hypervirulence determinants typically acquired via mobile genetic elements such as the well-characterised large virulence plasmid KpVP-1. The rmpADC locus is considered a key virulence feature of K. pneumoniae and is associated with upregulated capsule expression and the hypermucoid phenotype, which can enhance virulence by contributing to serum resistance. Typically such strains have been susceptible to all antimicrobials besides ampicillin, however the recent emergence of AMR hypermucoid strains is concerning. MethodsHere, we investigate the genetic diversity, evolution, mobilisation and prevalence of rmpADC, in a dataset of 14000 genomes from isolates of the Klebsiella pneumoniae species complex, and describe the RmST virulence typing scheme for tracking rmpADC variants for the purposes of genomic surveillance. Additionally, we examine the functionality of representatives for variants of rmpADC introduced into a mutant strain lacking its native rmpADC locus. ResultsThe rmpADC locus was detected in 7% of the dataset, mostly from genomes of K. pneumoniae and a very small number of K. variicola and K. quasipneumoniae. Sequence variants of rmpADC grouped into five distinct lineages (rmp1, rmp2, rmp2A, rmp3 and rmp4) that corresponded to unique mobile elements, and were differentially distributed across different populations (i.e. clonal groups) of K. pneumoniae. All variants were demonstrated to produce enhanced capsule production and hypermucoviscosity. ConclusionThese results provide an overview of the diversity and evolution of a prominent K. pneumoniae virulence factor and support the idea that screening for rmpADC in K. pneumoniae isolates and genomes is valuable to monitor the emergence and spread of hypermucoid K. pneumoniae, including AMR strains.

genomics↗