Biology subjects

Blane, B.

Publications and source records attributed to Blane, B..

7 recordsLinked to original sources

bioRxiv2026

Accounting for allelic diversity and multicopy gene detection improves the accuracy of antibiotic resistance genotypic determination

BackgroundGenomic prediction of antimicrobial resistance (AMR) relies on the accurate detection of resistance genes or allelic variants of core genes from raw or assembled genomes sequences. For several bacterial species and antibiotics, AMR genotype-phenotype discrepancies are common, indicating that important sources of error remain unresolved. For Enterococcus faecium, we focused on identifying the sources of discrepancies for tetracycline resistance, for which genotypic detection had shown particularly low accuracy. We investigated the effect of structural variation in antibiotic resistance genes (ARGs)--including gene duplications, truncations, interruptions, and mixed configurations of complete and partial gene copies-- as a source of genotype-phenotype discrepancies from short{square}read data. We conduct further extended investigations to other antibiotic families and into another bacterial species: Escherichia coli. MethodsWe analyzed collections of E. faecium and E. coli genomes, integrating high{square}quality complete assemblies, simulated Illumina short reads, and matched AMR phenotypic data. The integrity, copy number, and allelic diversity of ARGs were examined for multiple antibiotic classes, and their impact on ARG detection and accuracy of AMR determination was assessed using several commonly used bioinformatic tools (SRST2, ARIBA and AMRFinderPlus). ResultsFor E. faecium, after ruling out the effect of specific tet allelic variants on tetracycline susceptibility, we found that the integrity and copy number of tet(M) had a major effect on detection accuracy. Duplicated and incomplete ARGs are also common in E. faecium genomes, particularly for macrolides (erm(B)) and aminoglycosides (ant(6)-Ia and aph(3)-IIIa). In E. coli, similar patterns were observed for tet(A), erm(B) and aminoglycoside{square}associated genes (aph(3{square})-IIIa and ant(6)-Ia). Across ARGs in both species, short-read mapping methods wrongly reported interrupted genes as complete in some instances, while assembly{square}based methods often failed to resolve complete copies of duplicated genes. Detection accuracy improved when tools were adapted to account for gene integrity and when extended AMR databases incorporating species{square}specific alleles were included. ConclusionsOur findings reveal that bioinformatic limitations in dealing with ARG copy number and completeness, and in accounting for allelic variation, underly a substantial source of genotype-phenotype errors, highlighting the need for improved AMR databases and bioinformatic tools that consider these factors to achieve reliable genomic prediction of AMR.

bioinformatics↗

bioRxiv2025

BaGPipe: an automated, reproducible, and flexible pipeline for bacterial genome-wide association studies

Microbial genome-wide association study (GWAS) tools often require manual data processing steps, lack comprehensive workflows, and are limited by scalability issues, thus hindering the exploration of bacterial genetic traits. To address these challenges, we developed BaGPipe, an automated and flexible bacterial GWAS pipeline built using Nextflow and incorporating Pyseer for association analysis. BaGPipe integrates all essential components of a bacterial GWAS--spanning pre-processing, statistical analysis, and downstream visualisation--into a unified workflow that is reproducible and easy to deploy across diverse computational environments. BaGPipe was validated on a publicly available dataset of Streptococcus pneumoniae whole-genome sequences, and reproduced published findings with improved computational efficiency. BaGPipe was then applied to a dataset of Staphylococcus aureus whole-genome sequences, successfully identifying known and novel antibiotic resistance associations. By offering an accessible, efficient, and reproducible platform, BaGPipe accelerates bacterial GWAS and facilitates deeper exploration into the genetic underpinnings of phenotypic traits. Impact StatementThe increasing availability of bacterial genome sequences has created an opportunity for robust, reproducible tools to facilitate the discovery of novel genotype-phenotype associations. Despite the demonstrated utility of genome-wide association studies (GWAS) in identifying genetic determinants of disease, toxicity and antibiotic resistance, existing tools for bacterial GWAS often involve fragmented workflows requiring extensive manual intervention, limiting their adoption and reproducibility. Here, we introduce BaGPipe, a fully integrated bacterial GWAS pipeline that automates pre-processing, statistical analysis, and visualisation, thereby streamlining the entire workflow. With its flexibility, scalability, and ease of use, BaGPipe makes bacterial GWAS more accessible to researchers, enabling faster and more reliable insights into microbial genetics. This is an important step towards overcoming the computational and logistical barriers that have constrained bacterial GWAS, ultimately accelerating research into microbial evolution, resistance mechanisms, and the genetic basis of other key phenotypic traits. Data SummaryBaGPipe is freely available at https://github.com/sanger-pathogens/BaGPipe. The Streptococcus pneumoniae input dataset is available from the Pyseer tutorial (https://pyseer.readthedocs.io/en/master/tutorial.html#). The Staphylococcus aureus sequencing assemblies can be sourced from their ERS accession numbers provided in supplementary data. The reference assemblies, listed in the supplementary, can be sourced from NCBI.

bioinformatics↗

bioRxiv2023

The mutational landscape of Staphylococcus aureus during colonisation

Staphylococcus aureus is an important human pathogen but is primarily a commensal of the human nose and skin. Survival during colonisation is likely one of the major drivers of S. aureus evolution. Here we use a genome-wide mutation enrichment approach to analyse a genomic dataset of 3,060 S. aureus isolates from 791 individuals to show that despite limited within-host genetic diversity, an excess of protein-altering mutations can be found in genes encoding key metabolic pathways, in regulators of quorum-sensing and in known antibiotic targets. Nitrogen metabolism and riboflavin synthesis are the metabolic processes with strongest evidence of adaptation. Further evidence of adaptation to nitrogen availability was revealed by enrichment of mutations in the assimilatory nitrite reductase and urease, including mutations that enhance growth with urea as the sole nitrogen source. Inclusion of an additional 4,090 genomes from 802 individuals revealed eight additional genes including sasA/sraP, pstA, and rsbU with signals adaptive variation that warrant further characterisation. Our study provides the most comprehensive picture to date of the heterogeneity of adaptive changes that occur in the genomes of S. aureus during colonisation, revealing the likely importance of nitrogen metabolism, loss of quorum sensing and antibiotic resistance for successful human colonisation.

genomics↗

bioRxiv2021

Significant Variability exists in the Toxicity of Global Methicillin-resistant Staphylococcus aureus Lineages.

Staphylococcus aureus is a major human pathogen where the emergence of antibiotic resistant lineages, such as methicillin-resistant S. aureus (MRSA), is a major health concern. While some MRSA lineages are restricted to the healthcare setting, the epidemiology of MRSA is changing globally, with the rise of specific lineages causing disease in healthy people in the community. In the past two decades, community-associated MRSA (CA-MRSA) has emerged as a clinically important and virulent pathogen associated with serious skin and soft-tissue infections (SSTI). These infections are primarily toxin driven, leading to the suggestion that hyper-virulent lineages/multi-locus sequence types (STs) exist. To examine this, we compared the toxic activity of 475 MRSA isolates representing five major MRSA STs (ST22, ST93, ST8, ST239 and ST36) by employing a monocyte-macrophage THP-1 cell line as a surrogate for measuring gross cytotoxicity. We demonstrate that while certain MRSA STs contain highly toxic isolates, there is such variability within lineages to suggest that this aspect of virulence should not be inferred from the genotype of any given isolate. Furthermore, by interrogating the accessory gene regulator (Agr) sequences in this collection we identified several Agr mutations that were associated with reduced toxicity. Interestingly, the majority of isolates that were attenuated in toxin production contained no mutations in the agr locus, indicating a role of other undefined genes in S. aureus toxin regulation.

microbiology↗

bioRxiv2019

Contrasting approaches to genome-wide association studies impact the detection of resistance mechanisms in Staphylococcus aureus

Rapid detection of antibiotic resistance using whole-genome sequencing (WGS) could improve clinical outcomes and limit the spread of resistance. For this to succeed, we need an accurate way of linking genotype to phenotype, that identifies new resistance mechanisms as they appear. To assess how close we are to this goal, we characterized antimicrobial resistance determinants in >4,000 Staphylococcus aureus genomes of isolates associated with bloodstream infection in the United Kingdom and Ireland. We sought to answer three questions: 1) how well did known resistance mechanisms explain phenotypic resistance in our collection, 2) how many previously identified resistance mechanisms appeared in our collection, and 3) how many of these were detectable using four contrasting genome-wide association study (GWAS) methods. Resistance prediction based on the detection of known resistance determinants was 98.8% accurate. We identified challenges in correcting for population structure, clustering orthologous genes, and identifying causal mechanisms in rare or common phenotypes, which reduced the recovery of known mechanisms. Limited sensitivity and specificity of these methods made prediction using GWAS-discovered hits alone less accurate than using literature-derived genetic determinants. However, GWAS methods identified novel mutations associated with resistance, including five mutations in rpsJ, which improved tetracycline resistance prediction for 28 isolates, and a T118I substitution in fusA which resulted in better fusidic acid resistance prediction for 5 isolates. Thus, GWAS approaches in conjunction with phenotypic testing data can support the development of comprehensive databases to enable real-time use of WGS for patient management.

bioinformatics↗

bioRxiv2019

The emergence of successful Streptococcus pyogenes lineages through convergent pathways of capsule loss and recombination directing high toxin expression

Gene transfer and homologous recombination in Streptococcus pyogenes has the potential to trigger the emergence of pandemic lineages, as exemplified by lineages of emm1 and emm89 that emerged in the 1980s and 2000s respectively. Although near-identical replacement gene transfer events in the nga (NADase) and slo (Streptolysin O) locus conferring high expression of these toxins underpinned the success of these lineages, extension to other emm-genotype lineages is unreported. The emergent emm89 lineage was characterised by five regions of homologous recombination additional to nga/slo, including complete loss of the hyaluronic acid capsule synthesis locus hasABC, a genetic trait replicated in two other leading emm types and recapitulated by other emm types by inactivating mutations. We hypothesised that other leading genotypes may have undergone a similar recombination events. We analysed a longitudinal dataset of genomes from 344 clinical invasive disease isolates representative of locations across England, dating from 2001 to 2011, and an international collection of S. pyogenes genomes representing 54 different genotypes, and found frequent evidence of recombination events at the nga-slo locus predicted to confer higher toxin expression. We identified multiple associations between recombination at this locus and inactivating mutations within hasA/B, suggesting convergent evolutionary pathways in successful genotypes. This included common genotypes emm28 and emm87. The combination of no or low capsule, and high expression of nga and slo, may underpin the success for many emergent S. pyogenes lineages of different genotypes, triggering new pandemics and could change the way S. pyogenes causes disease.\n\nImportanceStreptococcus pyogenes is a genetically diverse pathogen, with over 200 different genotypes defined by emm typing, but only a minority of these genotypes are responsible for majority of human infection in high income countries. Two prevalent genotypes associated with disease rose to international dominance following recombination of a toxin locus that conferred increased expression. Here, we found that recombination of this locus and promoter has occurred in other diverse genotypes, events that may allow these genotypes to expand in the population. We identified an association between the loss of hyaluronic acid capsule synthesis and high toxin expression, which we propose may be associated with an adaptive advantage. As S. pyogenes pathogenesis depends both on capsule and toxin production, new variants with altered expression may result in abrupt changes in the molecular epidemiology of this pathogen in the human population over time.

microbiology↗

bioRxiv2018

One Health genomic surveillance of Escherichia coli demonstrates distinct lineages and mobile genetic elements in isolates from humans versus livestock

Livestock have been proposed as a reservoir for drug-resistant Escherichia coli that infect humans. We isolated and sequenced 431 E. coli (including 155 ESBL-producing isolates) from cross-sectional surveys of livestock farms and retail meat in the East of England. These were compared with the genomes of 1517 E. coli associated with bloodstream infection in the United Kingdom. Phylogenetic core genome comparisons demonstrated that livestock and patient isolates were genetically distinct, indicating that E. coli causing serious human infection do not directly originate from livestock. By contrast, we observed highly related isolates from the same animal species on different farms. Analysis of accessory (variable) genomes identified a virulence cassette associated previously with cystitis and neonatal meningitis that was only present in isolates from humans. Screening all 1948 isolates for accessory genes encoding antibiotic resistance revealed 41 different genes present in variable proportions of humans and livestock isolates. We identified a low prevalence of shared antimicrobial resistance genes between livestock and humans based on analysis of mobile genetic elements and long-read sequencing. We conclude that in this setting, there was limited evidence to support the suggestion that antimicrobial resistant pathogens that cause serious infection in humans originate from livestock.\n\nImportanceThe increasing prevalence of E. coli bloodstream infections is a serious public health problem. We used genomic epidemiology in a One Health study conducted in the East of England to examine putative sources of E. coli associated with serious human disease. E. coli from 1517 patients with bloodstream infection were compared with 431 isolates from livestock farms and meat. Livestock-associated and bloodstream isolates were genetically distinct populations based on core genome and accessory genome analyses. Identical antimicrobial resistance genes were found in livestock and human isolates, but there was little overlap in the mobile elements carrying these genes. In addition, a virulence cassette found in humans isolates was not identified in any livestock-associated isolate. Our findings do not support the idea that E. coli causing invasive disease or their resistance genes are commonly acquired from livestock.

genomics↗