Biology subjects

Bray, J. E.

Publications and source records attributed to Bray, J. E..

7 recordsLinked to original sources

bioRxiv2026

A Life Identification Number Barcoding (LIN Code) System for Neisseria meningitidis: high resolution multi-level typing of meningococci.

Neisseria meningitidis is a commensal member of the human oropharyngeal microbiota that can cause devastating invasive meningococcal disease. This genetically and antigenically diverse accidental pathogen has been a paradigm for the study of bacterial population biology. The meningococcus was the first organism for which a seven-locus multi-locus sequence typing (MLST) scheme was developed. With the addition of sequence-based characterisation of antigen genes, molecular typing has been widely employed to inform surveillance and public health interventions. Following the advent and widespread adoption of whole genome sequencing (WGS), precise delineation of variants is possible. Here, a WGS-based Life Identification Number (LIN) code typing scheme is described, providing a multi-resolution nomenclature for understanding meningococcal population diversity and molecular epidemiology. The LIN codes were developed using a set of 6,131 N. meningitidis genomes, comprising up to 200 isolates from each clonal complex (cc) previously described using MLST. Based on cluster-stability analysis and concordance with ccs, thirteen LIN thresholds described the meningococcal population at different levels of resolution. LIN codes and human-readable nicknames consistent with existent nomenclatures were assigned to the N. meningitidis genomes hosted in the PubMLST. Published outbreaks validated the LIN thresholds, illustrating the potential of this genomic tool in public health management.

microbiology↗

bioRxiv2025

Understanding the population structure of Moraxella catarrhalis using core genome multilocus sequence typing (cgMLST) and a life identification number (LIN) code classification system

Moraxella catarrhalis is an important cause of infectious exacerbations of chronic obstructive pulmonary disease and otitis media. Previously, seroresistant (SR) and serosensitive (SS) lineages that differed in virulence potential were described, which raised questions about their evolutionary relationship and species classification. To investigate the population structure of M. catarrhalis, we developed a core-genome multilocus sequence typing (cgMLST) scheme using 1,319 core genes, and a life identification number (LIN) barcode classification system. Whole-genome analyses of nearly 2,000 genomes confirmed two divergent SR and SS M. catarrhalis lineages with distinct evolutionary trajectories. SR genomes were more conserved, while SS genomes exhibited greater genetic variability. Virulence gene analyses revealed lineage-specific variations in ubiquitous surface proteins (UspA1 and UspA2) and lipooligosaccharide (LOS) types, and SR genomes had more diverse LOS variants. The bro {beta}-lactamase gene, and the mcb bacteriocin cluster, were more common in SR, which suggested different selective pressures and ecological adaptation. This cgMLST scheme and LIN code system provides a robust method for characterising M. catarrhalis, distinguishes between SR and SS lineages, and offers a unified framework for population structure analyses. Implemented within PubMLST, this open-access resource facilitates high-resolution genomic studies and supports the scientific community in understanding the evolutionary complexity of M. catarrhalis.

genomics↗

bioRxiv2025

Development of a core genome multilocus sequence typing (cgMLST) scheme and life identification number (LIN) code classification system for Staphylococcus aureus

Staphylococcus aureus infects both humans and animals, and antimicrobial resistance, including multidrug resistance, complicates treatment of S. aureus infections. Understanding S. aureus population structure and the distribution of genetic lineages is central to understanding the biology, epidemiology, and pathogenesis of this organism. This study exploited a large, publicly available dataset of nearly 27,000 S. aureus genomes to: i) develop a core genome multilocus sequence type (cgMLST) scheme; ii) stratify hierarchical clusters based on allelic similarity thresholds; and iii) define the clusters with a life identification number (LIN) code classification system. The cgMLST scheme characterised allelic variation at 1,716 core gene loci, and 13 classification thresholds were defined, which discriminated S. aureus variants across a range of genetic similarity thresholds. LIN code lineages and clonal complexes defined by seven-locus multilocus sequence typing were highly concordant, but the LIN codes permitted a wider range of genetic discrimination among S. aureus genomes. This S. aureus cgMLST scheme and LIN code system is a high-resolution, stable genotyping tool that enables detailed genomic analyses of S. aureus.

genomics↗

bioRxiv2023

Development of the Pneumococcal Genome Library, a core genome multilocus sequence typing scheme, and a taxonomic life identification number barcoding system to investigate and define pneumococcal population structure

Investigating the genomic epidemiology of major bacterial pathogens is integral to understanding transmission, evolution, colonisation, disease, antimicrobial resistance, and vaccine impact. Furthermore, the recent accumulation of large numbers of whole genome sequences for many bacterial species enhances the development of robust genome-wide typing schemes to define the overall bacterial population structure and lineages within it. Using previously published data, we developed the Pneumococcal Genome Library (PGL), a curated dataset of 30,976 genomes and contextual data for carriage and disease pneumococci recovered between 1916-2018 in 82 countries. We leveraged the size and diversity of the PGL to develop a core genome multilocus sequence typing (cgMLST) scheme comprised of 1,222 loci. Finally, using multilevel single-linkage clustering, we stratified pneumococci into hierarchical clusters based on allelic similarity thresholds, and defined these with a taxonomic life identification number (LIN) barcoding system. The PGL, cgMLST scheme, and LIN barcodes represent a high-quality genomic resource and fine-scale clustering approaches for the analysis of pneumococcal populations, which support the genomic epidemiology and surveillance of this leading global pathogen. Impact statementMany thousands of pneumococcal genomes are available in the public domain, and this creates opportunities for the scientific community to re-use existing data; however, these data are most useful when the contextual data (provenance and phenotype) are also linked to the genomes. Therefore, we created a curated, open-access database in PubMLST that contained nearly 31,000 published pneumococcal genomes and the corresponding contextual data for each genome. This large and diverse pneumococcal database was used to create a novel cgMLST scheme and multilevel clustering method to define genetic lineages with high resolution and a standardised nomenclature. These are open-access resources for all to use and provide a unified framework for the characterisation of global pneumococcal populations.

genomics↗

bioRxiv2022

First reported detection of the mobile colistin resistance genes, mcr-8 and mcr-9, in the Irish environment

The emergence and dissemination of mobile colistin resistance (mcr) genes across the globe poses a significant threat to public health, as colistin remains one of the last line treatment options for multi-drug resistant infections. Environmental samples (157 water and 157 wastewater) were collected in Ireland between 2018 and 2020. Samples collected were assessed for the presence of antimicrobial resistant bacteria using Brilliance ESBL, Brilliance CRE, mSuperCARBA and McConkey agar containing a ciprofloxacin disc. All water and integrated constructed wetland influent and effluent samples were filtered and enriched in buffered peptone water prior to culture, while wastewater samples were cultured directly. Isolates collected were identified via MALDI-TOF, were tested for susceptibility to 16 antimicrobials, including colistin, and subsequently underwent whole genome sequencing. Overall, eight mcr positive Enterobacterales (one mcr-8 and seven mcr-9) were recovered from six samples (freshwater (n=2), healthcare facility wastewater (n=2), wastewater treatment plant influent (n=1) and integrated constructed wetland influent (piggery farm waste) (n=1)). While the mcr-8 positive K. pneumoniae displayed resistance to colistin, all seven mcr-9 harbouring Enterobacterales remained susceptible. All isolates demonstrated multi-drug resistance and through whole genome sequencing analysis, were found to harbour a wide variety of antimicrobial resistance genes i.e., 30 {+/-} 4.1 (10-61), including the carbapenemases, blaOXA-48 (n=2) and blaNDM-1 (n=1), which were harboured by three of the isolates. The mcr genes were located on IncHI2, IncFIIK and IncI1-like plasmids. The findings of this study highlight potential sources and reservoirs of mcr genes in the environment and illustrate the need for further research to gain a better understanding of the role the environment plays in the persistence and dissemination of antimicrobial resistance.

microbiology↗

bioRxiv2019

Targeted metagenomic sequencing enhances the identification of pathogens associated with acute infection.

The routine identification of pathogens during infection remains challenging because it relies on multiple modalities such as culture and nucleic acid amplification and tests that tend to be specific for very few of an enormous number of possible infectious agents. Metagenomics promises single-test identification, but shotgun sequencing remains unwieldy and expensive or in many cases insufficiently sensitive to detect the amount of pathogen material in a clinical sample. Here we present the validation and application of Castanet, a method for metagenomic sequencing with enrichment that exploits clinical knowledge to construct a broad panel of relevant organisms for detection at low cost with sensitivity comparable to PCR. Castanet targets both DNA and RNA, works with small sample volumes, and can be implemented in a high-throughput diagnostic setting. We used Castanet to analyse plasma samples from 573 patients from the GAinS sepsis cohort and CSF samples from 243 patients from the ChiMES meningitis cohort that had been evaluated using standard clinical microbiology methods, identifying relevant pathogens in many cases where no pathogen had previously been detected. Castanet is intended for use in defining the distribution of pathogens in samples, diseases and populations, for large-scale clinical studies and for verifying the performance of routine testing regimens. By providing sequence as output, Castanet combines pathogen identification directly with subtyping and phylo-epidemiology.

microbiology↗

bioRxiv2017

Heterogeneity Among Estimates Of The Core Genome And Pan-Genome In Different Pneumococcal Populations

BackgroundUnderstanding the structure of a bacterial population is essential in order to understand bacterial evolution, or which genetic lineages cause disease, or the consequences of perturbations to the bacterial population. Estimating the core genome, the genes common to all or nearly all strains of a species, is an essential component of such analyses. The size and composition of the core genome varies by dataset, but our hypothesis was that variation between different collections of the same bacterial species should be minimal. To test this, the genome sequences of 3,121 pneumococci recovered from healthy individuals in Reykjavik (Iceland), Southampton (United Kingdom), Boston (USA) and Maela (Thailand) were analysed.\n\nResultsThe analyses revealed a supercore genome (genes shared by all 3,121 pneumococci) of only 303 genes, although 461 additional core genes were shared by pneumococci from Reykjavik, Southampton and Boston. Overall, the size and composition of the core genomes and pan-genomes among pneumococci recovered in Reykjavik, Southampton and Boston were very similar, but pneumococci from Maela were distinctly different. Inspection of the pan-genome of Maela pneumococci revealed several >25 Kb sequence regions that were homologous to genomic regions found in other bacterial species.\n\nConclusionsSome subsets of the global pneumococcal population are highly heterogeneous and thus our hypothesis was rejected. This is an essential point of consideration before generalising the findings from a single dataset to the wider pneumococcal population.

genomics↗