Biology subjects

Thorpe, H. A.

Publications and source records attributed to Thorpe, H. A..

11 recordsLinked to original sources

bioRxiv2025

Co-evolution between colibactin production and resistance is linked to clonal expansions in Escherichia coli

Specific strains of Escherichia coli employ the polyketide synthase island to produce a metabolite called colibactin that is implicated in colorectal tumorigenesis via its genotoxic effect on human DNA. However, the damage to host DNA is essentially collateral from ecological competition during bacterial colonisation, where colibactin is used to displace other gut bacteria. Despite intensive recent research on colibactin and its involvement in tumorigenesis, the evolutionary dynamics related to its production remain poorly characterised. We map evolution of colibactin production in E. coli using a large collection of high-resolution genomes and show that its introduction via a mobile element has induced multiple plasmid-mediated acquisitions of previously unrecognised colibactin immunity genes in non-producing multi-drug resistant lineages. Our study suggests that in E. coli, multi-drug resistance is incompatible with colibactin production due to the unbearable combined fitness costs, supported by colibactin-producing phenotypes remaining susceptible to most classes of antibiotics and thriving in regions with low antimicrobial usage. Consequently, resistant lineages circulating in these regions are under selective pressure to acquire colibactin immunity to compete with the endemic colibactin-producing bacteria during colonisation. Conversely, high antimicrobial usage selects for a colibactin susceptible antimicrobial resistant phenotype as it drives the colibactin-producing E. coli towards extinction. Such a duality of evolutionary strategies to become endemic in a host population structured by varying ecological pressures may hold more generally across bacterial species colonizing the human gut.

microbiology↗

bioRxiv2025

High frequency body site translocation of nosocomial Pseudomonas aeruginosa

Pseudomonas aeruginosa is an important nosocomial pathogen which can cause serious infections across diverse anatomic locations. Infections can spread within an individual to different body sites, but the rate and directionality of this process is unknown. We explored within-host diversity as well as the body site translocation dynamics using de-convoluted metagenomic P. aeruginosa reads from 256 hospital patients sampled at both respiratory and gut sites. Of the 84 patients where P. aeruginosa genomes could be recovered, there were 27 cases where the same P. aeruginosa clone was detected across multiple body sites. Using a simulation approach, we found that the majority of body site sharing was likely due to within-patient translocation of clones rather than independent acquisition from the hospital environment. Using ancestral reconstruction, we predicted that most clones likely occupied a respiratory niche, and that the probable direction of clone transmission was lung-to-gut. We detected within-patient variation and noted a strong enrichment of mutations in genes associated with antimicrobial resistance, irrespective of sample type. There was significantly more translocation than has been previously reported and highlight that lower respiratory tract infections can result in persistent gut colonisation of P. aeruginosa, a major risk factor for sepsis in vulnerable hosts.

microbiology↗

bioRxiv2024

Enhanced metagenomics-enabled transmission inference with TRACS

Coexisting strains of the same species within the human microbiota pose a substantial challenge to inferring the host-to-host transmission of both pathogenic and commensal microbes. Here, we present TRACS, a highly accurate algorithm for estimating genetic distances between strains at the level of individual SNPs, which is robust to intra-species diversity within the host. Analysis of well-characterised Faecal Microbiota Transplantation datasets, along with extensive simulations, demonstrates that TRACS substantially outperforms existing strain aware transmission inference methods. We use TRACS to infer transmission networks in patients colonised with multiple strains, including SARS-CoV-2 amplicon sequencing data from UK hospitals, deep population sequencing data of Streptococcus pneumoniae and single-cell genome sequencing data from malaria patients infected with Plasmodium falciparum. Applying TRACS to gut metagenomic samples from a large cohort of 176 mothers and 1,288 infants born in UK hospitals revealed species-specific transmission rates between mothers and their infants. Notably, TRACS identified increased persistence of Bifidobacterium breve in infants, a finding missed by previous analyses due to the presence of multiple strains.

bioinformatics↗

bioRxiv2023

Escherichia coli plasmidome maps the game of clones

Escherichia coli is the most widely studied microbe in history, but its extrachromosomal elements known as plasmids remain poorly delineated. Here we used long-read technology to high-resolution sequence the entire plasmidome and the corresponding host chromosomes from an unbiased longitudinal survey covering two decades and over 2,000 E. coli isolates. We find that some plasmids have persisted in lineages even for centuries, demonstrating strong plasmid-lineage associations. Our analysis provides a detailed map of recent vertical and horizontal evolutionary events involving plasmids with key antibiotic resistance, competition and virulence determinants. We present genomic evidence of both chromosomal and plasmid-driven success strategies that represent convergent phenotypic evolution in distant lineages, and use in vitro experiments to verify the importance of bacteriocin-producing plasmids for clone success. Our study has general implications for understanding plasmid biology and bacterial evolutionary strategies.

microbiology↗

bioRxiv2023

Detecting co-selection through excess linkage disequilibrium in bacterial genomes

Population genomics has revolutionised our ability to study bacterial evolution by enabling data-driven discovery of the genetic architecture of trait variation. Genome-wide association studies (GWAS) have more recently become accompanied by genome-wide epistasis and co-selection (GWES) analysis, which offers a phenotype-free approach to generating hypotheses about selective processes that simultaneously impact multiple loci across the genome. However, existing GWES methods only consider associations between distant pairs of loci within the genome due to the strong impact of linkage-disequilibrium (LD) over short distances. Based on the general functional organisation of genomes it is nevertheless expected that the majority of co-selection and epistasis will act within relatively short genomic proximity, on co-variation occurring within genes and their promoter regions, and within operons. Here we introduce LDWeaver, which enables an exhaustive GWES across both short- and long-range LD, to disentangle likely neutral co-variation from selection. We demonstrate the ability of LDWeaver to efficiently generate hypotheses about co-selection using large genomic surveys of multiple major human bacterial pathogen species and validate several findings using functional annotation and phenotypic measurements. Our approach will facilitate the study of bacterial evolution in the light of rapidly expanding population genomic data.

bioinformatics↗

bioRxiv2022

Strong pathogen competition in neonatal gut colonisation

Bacterial pathogen species and their strains that colonise the human gut are generally understood to compete against both each other and the commensal species colonising this ecosystem. However, currently we are lacking a population-wide quantification of strain-level colonisation dynamics for many common bacterial pathogens and the relationship of colonisation potential to prevalence in disease is unknown. In addition, it is unclear how ecological factors might be modulating the dynamics. Here, using a combination of latest high-resolution metagenomics and strain-level genomic epidemiology methods leveraging large genomic reference libraries of key pathogens, we performed a characterisation of the competition (co-exclusion and co-presence) and colonisation dynamics for a longitudinal cohort of neonatal gut microbiomes. We found a strong inter- and intra-species competition dynamic in the gut colonisation process, but also a number of synergistic relationships among several species belonging to genus Klebsiella, which includes the prominent human pathogen Klebsiella pneumoniae. Additionally, we find no evidence of preferential colonisation by hospital-adapted pathogen lineages in either vaginal or caesarean section birth groups. Our analysis also enables the first unbiased assessment of the strain-level colonisation potential of extra-intestinal pathogenic Escherichia coli (ExPEC) in comparison with their potential to cause bloodstream infections. We determined that the established common ExPEC clones ST73 and ST95 are overall significantly more pathogenic than the more recent, globally circulating multi-drug resistant clone ST131, where only a single subclone (ST131-C2) exhibited excess pathogenic potential. Our study highlights the importance of systematic surveillance of bacterial gut pathogens, not only from disease but also from carriage state, to better inform therapies and preventive medicine in the future.

microbiology↗

bioRxiv2021

One Health or Three? Transmission modelling of Klebsiella isolates reveals ecological barriers to transmission between humans, animals and the environment

The Klebsiella group is highly diverse both genetically and ecologically, being commonly recovered from humans, livestock, plants, soil, water, and wild animals. Many species are opportunistic pathogens, and can harbour diverse classes of antimicrobial resistance (AMR) genes. K. pneumoniae is responsible for a high public-health burden, due in part to the rapid spread of health-care associated clones that are non-susceptible to carbapenems. Klebsiella thus represents a highly pertinent taxon for assessing the risk to public health posed by animal and environmental reservoirs. Here we report an analysis of 6548 samples and 3,482 genome sequences representing 15 Klebsiella species sampled over a 15-month period from a wide range of clinical, community, animal and environmental settings in and around the city of Pavia, in the northern Italian region of Lombardy. Despite carbapenem-resistant clones circulating at a high frequency in the hospitals, we find no genotypic or phenotypic evidence for non-susceptibility to carbapenems outside of the clinical environment. The non-random distribution of species and strains across sources point to ecological barriers that are likely to limit AMR transmission. Although we find evidence for occasional transmission between settings, hierarchical modelling and intervention analysis suggests that direct transmission from the multiple non-human (animal and environmental) sources included in our sample accounts for less than 1% of hospital disease, with the vast majority of clinical cases originating from other humans.

microbiology↗

bioRxiv2020

Quantifying bacterial evolution in the wild: a birthday problem for Campylobacter lineages

Measuring molecular evolution in bacteria typically requires estimation of the rate at which nucleotide changes accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the birthday problem. Using large genomic datasets and comparative genomic approaches, we use isolate pairs that share recent common ancestry to estimate the rate of nucleotide change for the population. Identifying synonymous and non-synonymous nucleotide changes, both within and outside of recombined regions of the genome, we quantify clock-like diversification to estimate synonymous rates of nucleotide change for the common pathogenic bacteria Campylobacter coli (2.4 x 10-6 s/s/y) and Campylobacter jejuni (3.4 x 10-6 s/s/y). Finally, using estimated total rates of nucleotide change, we infer the number of effective lineages within the sample time-frame - analogous to a shared birthdays - and assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalizable approach to calibrating rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species. Author SummaryGrowth and reproduction in living organisms require DNA replication but this process is error prone. Along with variation introduced by horizontal gene transfer, it can lead to alterations in the nucleotide sequence. These nucleotide changes accumulate over time in successive generations at an approximately constant rate termed the molecular clock. Therefore, if this rate is known, one can estimate the date when two or more lineages diverged. In bacteria, this can be informative for understanding the time-scale of emergence and spread of pathogenic strains. Such analyses are robust when the ancestral population is known, such as for obligate pathogens that only infect humans. However, when the bacterium inhabits multiple hosts or niches it is difficult to infer direct ancestry from one strain to another, reducing the accuracy of molecular clock estimates. Here we focus on one such multi-host organism, Campylobacter, a leading cause of food-borne gastroenteritis. Reconstructing the population history by estimating empirical nucleotide change rates from carefully selected isolate pairs, and evaluating the maintenance of multiple lineages over time, we provide information about strain diversification. Our method is a new addition to the bacterial genomics toolkit that will help in understanding the spread of opportunistic pathogens.

genomics↗

bioRxiv2019

Description of Klebsiella spallanzanii sp. nov. and of Klebsiella pasteurii sp. nov.

Klebsiella oxytoca causes opportunistic human infections and post-antibiotic haemorrhagic diarrhoea. This Enterobacteriaceae species is genetically heterogeneous and is currently subdivided into seven phylogroups (Ko1 to Ko4, Ko6 to Ko8). Here we investigated the taxonomic status of phylogroups Ko3 and Ko4. Genomic sequence-based phylogenetic analyses demonstrate that Ko3 and Ko4 formed well-defined sequence clusters related to, but distinct from, Klebsiella michiganensis (Ko1), Klebsiella oxytoca (Ko2), K. huaxiensis (Ko8) and K. grimontii (Ko6). The average nucleotide identity of Ko3 and Ko4 were 90.7% with K. huaxiensis and 95.5% with K. grimontii, respectively. In addition, three strains of K. huaxiensis, a species so far described based on a single strain from a urinary tract infection patient in China, were isolated from cattle and human faeces. Biochemical and MALDI-ToF mass spectrometry analysis allowed differentiating Ko3, Ko4 and Ko8 from the other K. oxytoca species. Based on these results, we propose the names Klebsiella spallanzanii for the Ko3 phylogroup, with SPARK_775_C1T (CIP 111695T, DSM 109531T) as type strain, and Klebsiella pasteurii for Ko4, with SPARK_836_C1T (CIP 111696T, DSM 109530T) as type strain. Strains of K. spallanzanii were isolated from human urine, cow faeces and farm surfaces, while strains of K. pasteurii were found in faecal carriage from humans, cows and turtles.\n\nAccession numbersThe nucleotide sequences generated in this study were deposited in ENA and are available through the INSDC databases under accession numbers MN091365 (SB6411T = SPARK775C1T), MN091366 (SB6412 T = SPARK836C1T) and MN104661 to MN104677 (16S rRNA), MN076606 to MN076643 (gyrA and rpoB), and MN030558 to MN030567 (blaOXY). Complete genomic sequences were submitted to European Nucleotide Archive under the BioProject number PRJEB15325.\n\nAbbreviationsANI, average nucleotide identity; HCCA, a-cyano-4-hydroxycinnamic acid; isDDH, in silico DNA-DNA hybridization; SCAI, Simmons citrate agar with inositol; MALDI57 ToF MS: Matrix-assisted laser desorption/ionization time of flight mass spectrometry

microbiology↗

bioRxiv2019

PIRATE: A fast and scalable pangenomics toolbox for clustering diverged orthologues in bacteria

Cataloguing the distribution of genes within natural bacterial populations is essential for understanding evolutionary processes and the genetic basis of adaptation. Here we present a pangenomics toolbox, PIRATE (Pangenome Iterative Refinement And Threshold Evaluation), which identifies and classifies orthologous gene families in bacterial pangenomes over a wide range of sequence similarity thresholds. PIRATE builds upon recent scalable software developments to allow for the rapid interrogation of thousands of isolates. PIRATE clusters genes (or other annotated features) over a wide range of amino-acid or nucleotide identity thresholds and uses the clustering information to rapidly classify paralogous gene families into either putative fission/fusion events or gene duplications. Furthermore, PIRATE orders the pangenome using a directed graph, provides a measure of allelic variation and estimates sequence divergence for each gene family. We demonstrate that PIRATE scales linearly with both number of samples and computation resources, allowing for analysis of large genomic datasets, and compares favorably to other popular tools. PIRATE provides a robust framework for analysing bacterial pangenomes, from largely clonal to panmictic species.\n\nAvailabilityPIRATE is implemented in Perl and is freely available under an GNU GPL 3 open source license from https://github.com/SionBayliss/PIRATE.\n\nSupplementary InformationSupplementary data is available online.

bioinformatics↗

bioRxiv2017

Piggy: A Rapid, Large-Scale Pan-Genome Analysis Tool for Intergenic Regions in Bacteria

Despite overwhelming evidence that variation in intergenic regions (IGRs) in bacteria impacts on phenotypes, most current approaches for analysing pan-genomes focus exclusively on protein-coding sequences. To address this we present Piggy, a novel pipeline that emulates Roary except that it is based only on IGRs. We demonstrate the use of Piggy for pan-genome analyses of Staphylococcus aureus and Escherichia coli using large genome datasets. For S. aureus, we show that highly divergent (\"switched\") IGRs are associated with differences in gene expression, and we establish a multi-locus reference database of IGR alleles (igMLST; implemented in BIGSdb). Piggy is available at https://github.com/harry-thorpe/piggy.

genomics↗