Biology subjects

Croucher, N. J.

Publications and source records attributed to Croucher, N. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Identifying candidate genetic determinants associated with invasion in pneumococcal lineages

Serotype invasiveness estimates help identify high-risk serotypes and interpret disease replacement following pneumococcal conjugate vaccination. Because serotype and lineage are strongly associated, their independent contributions must be separated to identify unexpectedly invasive lineages and investigate underlying mechanisms. Using temporally matched carriage and invasive-disease isolates from children aged <7 years in South Africa and the USA, we fitted a logistic mixed-effects model with Global Pneumococcal Sequence Cluster (GPSC) as a random effect and serotype and country as fixed effects. We conducted a species-wide genome-wide association study (GWAS) of invasion and compared the prevalence of significant unitigs in GPSC1 and GPSC21 to identify invasion-associated variants differentiating them. We additionally examined capsule-locus variation that could contribute to their contrasting invasiveness. After serotype and country adjustment, GPSC1 and GPSC21, which both express 19F and share an immediate common ancestor, ranked fifth and 149th of 150 lineages; odds multipliers were 1.51 (95% conditional interval 1.06-2.15) and 0.61 (0.41-0.93), respectively. Of 1,569 invasion-associated unitigs from the species-wide GWAS, 272 differentiated GPSC1 from GPSC21. Among these, the strongest signal mapped to hk11 (desK) and was associated with GPSC1; bgaA was the highest-ranked known antibody-binding target. Within GPSC1 CC271 had additional variants in the ATP-dependent Clp protease ATP-binding subunit ClpX compared to the CC420 subclade. Capsule-protein folds were conserved with local effects indistinguishable from prediction uncertainty. Separating serotype and lineage effects can identify unexpectedly invasive lineages and prioritize candidate serotype-independent determinants, vaccine antigens and capsule variation for experimental investigation.

microbiology↗

bioRxiv2026

The global evolutionary dynamics of natural capsule switching in a human-restricted bacterial pathogen

Exchange of genetic loci encoding extracellular capsular polysaccharides in bacteria can change capsular antigens or serotype, which, in turn, can lead to evasion of vaccines targeting the capsule. However, the evolutionary dynamics and drivers of bacterial capsule switching remain poorly understood. Here, we investigate the evolutionary dynamics and correlates of capsule switching in bacteria, using the human-restricted bacterial pathogen Streptococcus pneumoniae as an example, using 10,558 genetically and geographically diverse whole-genome sequences. Our phylogenomic and ancestral state reconstruction analysis revealed that the propensity for capsule switching varies by capsule type and genetic background. We found capsule switches only between ~4% of all possible capsule-type pairs, varying by specific pairs and switching direction. We also found associations between capsule switching patterns and genetic and ecological factors, including nasopharyngeal carriage duration, capsule biosynthesis locus size, and capsule thickness. Furthermore, the genetic similarity of the replacing and replaced capsule loci was primarily associated with the frequency of switching between specific capsule type pairs. Although a few specific non-capsule genomic loci were associated with the propensity for capsule switching across distinct lineages, the collective effect of the genetic background appears to influence capsule switching more strongly. These findings shed light on how bacterial capsule types and lineages undergo capsule switching influenced by genetic and ecological factors, informing our understanding of the emergence of novel capsule-genotype combinations that may impact the design of capsule-targeting glycoconjugate vaccines.

microbiology↗

bioRxiv2026

Rapid gene exchange explains differences in bacterial pangenome structure

The size and diversity of bacterial gene repertoires, known as pangenomes, vary widely across species. The evolutionary forces driving the maintenance of pangenomes is an open topic of debate, with contradictory theories suggesting that pangenomes exist as a result of neutral evolution, with all genes gained and lost at random, or that all genes provide a fitness benefit to the host and are maintained by positive selection. Modelling of pangenome dynamics has provided insight into how gene exchange explains observed gene frequency distributions, and stands as the only means of jointly inferring contributions of individual gene selection effects and mobility on the maintenance of pangenomes. However, previous modelling studies have not included both gene-level selection and mobility, and do not consider broadly sampled genome datasets for many species. To differentiate neutral and selective forces maintaining pangenomes, we developed a mechanistic model of gene-level evolution, Pansim, and a scalable model fitting framework, PopPUNK-mod. Together, these tools leverage rapid genome distance calculation to fit models of pangenome dynamics to datasets containing hundreds of thousands of genomes. We used this framework to compare the pangenome dynamics of over 400 different bacterial species, using over 600,000 genomes. We find that diversity in pangenome characteristics between species is driven predominantly by variation in the number of rapidly exchanged genes, while the rate of exchange of remaining genes is conserved. We find that bacterial phylogeny, rather than ecology, correlates with pangenome dynamics. We express that pan-species gene-level analyses are now needed to understand selection across accessory genes. Our work highlights the importance of gene exchange rate differences in governing differences in pangenome characteristics between species.

bioinformatics↗

bioRxiv2025

A reusable model of pangenome selection informs optimal surveillance strategies over vaccine introductions

BackgroundThe human pathogen Streptococcus pneumoniae is a major cause of disease, including pneumonia and meningitis. The introduction of Pneumococcal Conjugate Vaccines (PCVs) initially reduced the burden of disease through a reduction of colonisation by vaccine-targeted serotypes. However, since PCVs only target a proportion of pneumococcal serotypes, they shift intraspecific competition, eventually allowing non-targeted types to replace vaccine types. Understanding the host and pathogen factors causing replacement is important for future vaccine development. Mechanistic understanding of vaccine replacement dynamics is crucial for forecasting and optimisation of genomic surveillance strategies to evaluate realised vaccine effectiveness. MethodsWe developed a mathematical model of the genomic and demographic factors which explain vaccine replacement, used this model to replicate serotype-frequency changes, and investigated cost-effective genomic surveillance strategies. We extended a forward-time model based on the Wright-Fisher model, developing a user-friendly model framework that describes the post-vaccine dynamics of S. pneumoniae populations. Our model describes vaccine replacement as a function of vaccine impact, immigration of new strains, and negative frequency-dependent selection (NFDS) on the accessory genome content. ResultsWe used our model to study vaccine replacement in newly sequenced genomic surveillance data from Nepal, and existing data from the US, and the UK, with distinct surveillance strategies. We showed that the model with NFDS better replicates replacement dynamics than a null model without NFDS, and that NFDS likely only acts on part of the S. pneumoniae accessory genome. We found consistent estimates for vaccination effectiveness across the different study locations and country-specific genes under NFDS, highlighting the importance of conducting genomic surveillance in each country of interest. By simulating data from the model, we showed that an optimal surveillance strategy prioritises per-sampling sample size over sampling frequency for small sampling budgets. ConclusionsOur model can be used to predict vaccine replacement dynamics after PCV introduction, and can be easily reapplied to analyse new data from vaccine introductions or new regions. Our model is available in the R package STUBENTIGER (Studying Balancing Evolution (NFDS) To Investigate Genome Replacement) on GitHub https://github.com/bacpop/Stubentiger.

genomics↗

bioRxiv2025

Pneumococcal chromosome conformation variation between epigenetic variants is driven by episomal mobile genetic elements

Streptococcus pneumoniae (pneumococcus) is a genetically diverse opportunistic bacterial pathogen that expresses two phase-variable loci encoding restriction-modification systems. Comparisons of two genetically-distinct pairs of epigenetically-distinct variants, each distinguished by a stabilised arrangement of one of these phase-variable loci, found the consequent changes in genome-wide DNA methylation patterns were associated with differential expression of mobile genetic elements (MGEs). This relationship was hypothesised to be mediated through changes in xenogenic silencing (XS) or nucleoid organisation. Therefore the chromosomal conformation of the both variants of each isolate were characterised using Illumina Hi-C, and Nanopore Pore-C, sequencing. Both methods concurred that the organisation of the pneumococcal chromosome was dominated by small-scale structures, with most pairwise interactions between loci <25 kb apart. Neither found substantial evidence for higher-order structure or XS in the pneumococcal genome, with more complex contact patterns only evident around the replication origin. Comparisons between the variants identified phage-related chromosomal islands (PRCIs) as the foci of differential contact densities between the variants. This was driven by copy number variation, resulting from variable excision and replication of the episomal PRCIs. However, the methods were discordant in their identification of the variant in which the PRCI was more actively replicating in both pairs. Validatory experiments demonstrated that the prevalence of circular PRCIs was not determined by DNA modification, but instead varied stochastically between colonies in both backgrounds, and was metastable during vegetative growth. PRCI excision was inducible by mitomycin C, but independent of the presence of a phage. Yet transcriptional activation of these elements was affected by both signals, indicating transcription and replication are separately regulated. Therefore pneumococcal MGEs do not appear to be subject to XS, resulting in heterogeneity being generated within these bacterial populations through the frequent local disruption of chromosome conformation resulting from the stochastic excision and reintegration of episomal elements. Author summaryThe pneumococcus is a bacterium with a circular chromosome that is organised by DNA-binding proteins and often contains mobile genetic elements (MGEs), genes able to transmit between bacteria. All pneumococci encode defences against MGEs, some of which create epigenetic modifications (typically methylation) genome-wide at particular sequence motifs. Changes in these epigenetic patterns are associated with altered MGE gene expression and replication in otherwise genetically-identical bacteria. To test whether this was the result of methylation remodelling the organisation of the chromosome, we compared the contact patterns across the chromosome using two sequencing technologies. Both methods concurred that the pneumococcal genome is generally folded into small structures, with the biggest differences between the variants caused by the replication of MGEs. However, the methods disagreed on the variant in which the MGEs replicated fastest. Further experiments showed that MGE replication was stable over the course of culturing over hours, but would randomly change level between days, explaining the inconsistent observations. MGE replication was found to rise in response to DNA damage, whereas gene expression also depended on the presence of other signals, explaining the discrepancies in these activities between variants. Hence MGEs significantly contribute to the heterogeneity that rapidly accumulates within pneumococcal populations.

genomics↗

bioRxiv2024

Integrated population clustering and genomic epidemiology with PopPIPE

Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations, and as an additional source of information when detecting possible transmission events. Due to their variable gene content and order, reference-free methods offer more sensitive detection of genetic differences, especially among closely related samples found in outbreaks. However, across longer genetic distances, frequent recombination can make calculation and interpretation of these differences more challenging, requiring significant bioinformatic expertise and manual intervention during the analysis process. Here we present a Population analysis PIPEline (PopPIPE) which combines rapid reference-free genome analysis methods to analyse bacterial genomes across these two scales, splitting whole populations into subclusters and detecting plausible transmission events within closely related clusters. We use k-mer sketching to split populations into strains, followed by split k-mer analysis and recombination removal to create alignments and subclusters within these strains. We first show that this approach creates high quality subclusters on a population-wide dataset of Streptococcus pneumoniae. When applied to nosocomial vancomycin resistant Enterococcus faecium samples, PopPIPE finds transmission clusters which are more epidemiologically plausible than core genome or MLST-based approaches. Our pipeline is rapid and reproducible, creates interactive visualisations, and can easily be reconfigured and re-run on new datasets. Therefore PopPIPE provides a user-friendly pipeline for analyses spanning species-wide clustering to outbreak investigations. Impact statementAs time passes, bacterial genomes accumulate small changes in their sequence due to mutations, or larger changes in their content due to horizontal gene transfer. Using their genome sequences, it is possible to use phylogenetics to work out the most likely order in which these changes happened, and how long they took to happen. Then, one can estimate the time that separates any two bacterial samples - if it is short then they may have been directly transmitted or acquired from the same source; but if it is long they must have been acquired separately. This information can be used to determine transmission chains, in conjunction with dates and locations of infections. Understanding transmission chains enables targeted infection control measures. However, correctly calculating the genetic evidence for transmission is made difficult by correctly distinguishing different types of sequence changes, dealing with large amounts of genome data, and the need to use multiple complex bioinformatic tools. We addressed this gap by creating a computational workflow, PopPIPE, which automates the process of detecting possible transmissions using genome sequences. PopPIPE applies state-of-the-art tools and is fast and easy to run - making this technology will be available to a wider audience of researchers. Data summaryThe code for this pipeline is available at https://github.com/bacpop/PopPIPE and as a docker image https://hub.docker.com/r/poppunk/poppipe. Raw sequencing reads for Enterococcus faecium isolates have been deposited at the NCBI under BioProject accession number PRJNA997588.

bioinformatics↗

bioRxiv2024

The major pathogen Haemophilus influenzae experiences pervasive recombination and purifying selection at local and global scales

Haemophilus influenzae is a major opportunistic human pathogen which causes both non-invasive and invasive disease. The H. influenzae type b (Hib) vaccine has led to a significant reduction of invasive Hib disease, but offers no protection against colonisation or disease by unencapsulated non-typeables (NT) or non-b serotypes, and H. influenzae remains a public health burden worldwide, with increasing reports of multi-drug resistance (MDR). Despite this, there is no comprehensive understanding of the species global population structure. To advance understanding about the evolution and epidemiology of the species, we whole-genome sequenced 4,475 isolates of H. influenzae from an unvaccinated paediatric carriage and pneumonia cohort from northwestern Thailand. Despite no Hib immunisation, serotype b was uncommonly found (5.7%), while 91.7% of isolates were NT. We identified a large number of nearly pan-resistant lineages that were mostly NT, and discovered that no lineages were enriched among disease samples, suggesting the ability to cause invasive disease is not restricted to any subpopulation of the species. Extensive population genetic analyses of our data combined with a worldwide collection of 5,976 published genomes revealed a highly admixed population structure, low core genome nucleotide diversity, and evidence of pervasive negative selection. The combined data confirm that MDR lineages are not confined to our cohort, and their establishment globally is an urgent concern.

microbiology↗

bioRxiv2024

Chromosomal curing drives prophage evolution and bacterial epidemiology

Transformation occurs when bacteria import exogenous DNA via the competence machinery and integrate it into their genome through homologous recombination (HR). This process may provide an evolutionary advantage to cells through enabling "chromosomal curing": the deletion of integrative mobile genetic elements (MGEs). However, many such MGEs are sensitive to RecA-DNA filaments, triggering activation of a lifecycle that may enable them to evade HR-mediated deletion. Despite >40% of isolates containing prophage integrated at a site that inhibits transformation, three representative prophage were identified in naturally-competent pneumococci to test this hypothesis. These encompassed representatives with C1-type and ImmAR-type regulatory systems, found in almost all pneumococcal prophage. All three prophage were deleted by HR with an efficiency similar to the transfer of base substitutions. Mutations that impaired a C1-regulated prophage increased this deletion rate, reflecting this element being activated by RecA-DNA filaments imported during transformation, likely preferentially killing cells that induce competence. ImmAR-regulated prophage instead responded to transient stimuli by excising as deletion-resistant pseudolysogens, only driving cell lysis in response to sustained stimuli. This was likely a consequence of these prophage reacting to multiple signals, as they differed in their response to both RecA and the DNA-binding protein and competence repressor DprA. One prophage constitutively elevated host DprA levels, thereby reducing transformation by preventing induction of the competence machinery. Hence these data are consistent with an evolutionary arms race between prophage and the competence machinery, resulting in bacterial diversification though HR being impeded by MGEs preventing their own elimination from the chromosome.

microbiology↗

bioRxiv2024

Comparison of gene-by-gene and genome-wide short nucleotide sequence based approaches to define the global population structure of Streptococcus pneumoniae

Defining the population structure of a pathogen is a key part of epidemiology, as genomically related isolates are likely to share key clinical features such as antimicrobial resistance profiles and invasiveness. Multiple different methods are currently used to cluster together closely- related genomes, potentially leading to inconsistency between studies. Here, we use a global dataset of 26,306 S. pneumoniae genomes to compare four clustering methods: gene-by- gene seven-locus multi-locus sequencing typing (MLST), core genome MLST (cgMLST)- based hierarchical clustering (HierCC) assignments, Life Identification Number (LIN) barcoding, and k-mer-based PopPUNK clustering (known as GPSCs in this species). We compare the clustering results with phylogenetic and pan-genome analyses to assess their relationship with genome diversity and evolution, as we would expect a good clustering method to form a single monophyletic cluster that has high within-cluster similarity of genomic content. We show that the four methods are generally able to accurately reflect the population structure based on these metrics, and that the methods were broadly consistent with each other. We investigated further to study the discrepancies in clusters. The greatest concordance was seen between LIN barcoding and HierCC (Adjusted Mutual Information Score = 0.950), which was expected given that both methods utilise cgMLST, but have different methods for defining an individual cluster and different core genome schema. However, the existence of differences between the two methods show that the selection of a core genome schema can introduce inconsistencies between studies. GPSC and HierCC assignments were also highly concordant (AMI = 0.946), showing that k-mer based methods which use the whole genome and do not require the careful selection of a core genome schema are just as effective at representing the population structure. Additionally, where there were differences in clustering between these methods, this could be explained by differences in the accessory genome that were not identified in cgMLST. We conclude that for S. pneumoniae, standardised and stable nomenclature is important as the number of genomes available expands. Furthermore, the research community should transition away from seven- locus MLST, and cgMLST, GPSC, and LIN assignments should be used more widely. However, to allow for easy comparison between studies and to make previous literature relevant, the reporting of multiple clustering names should be standardised within research. Data summaryGenome sequences are deposited in the European Nucleotide Archive (ENA); accession numbers. Metadata of the pneumococcal isolates in this study have been submitted as a supplementary file and are also available on the Monocle Database available at https://data.monocle.sanger.ac.uk/. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Impact StatementUsing a global dataset of S. pneumoniae genomes allows us to thoroughly observe and analyse discrepancies between different clustering methods. Whilst all methods in this study are used to cluster S. pneumoniae genomes, no study has yet thoroughly compared the clustering results and discrepancies. This work summarises the strengths and weaknesses of the different methods and highlights the need for consistency between studies.

genomics↗

bioRxiv2024

Seamless, rapid and accurate analyses of outbreak genomic data using Split K-mer Analysis (SKA)

Sequence variation observed in populations of pathogens can be used for important public health and evolution genomic analyses, especially outbreak analysis and transmission reconstruction. Identifying this variation is typically achieved by aligning sequence reads to a reference genome, but this approach is susceptible to reference biases and requires careful filtering of called genotypes. Additionally, while the volume of bacterial genomes continues to grow, tools which can accurately and quickly call genetic variation between sequences have not kept pace. There is a need for tools which can process this large volume of data, providing rapid results, but remain simple so they can be used without highly trained bioinformaticians, expensive data analysis, and long term storage and processing of large files. Here we describe Split K-mer Analysis (SKA2), a method which supports both reference-free and reference-based mapping to quickly and accurately genotype populations of bacteria using sequencing reads or genome assemblies. SKA2 is highly accurate for closely related samples, and in outbreak simulations we show superior variant recall compared to reference-based methods, with no false positives. We also show that within bacterial strains, where it is possible to construct a clonal frame, SKA2 can also accurately map variants to a reference, and be used with recombination detection methods to rapidly reconstruct vertical evolutionary history. SKA2 is many times faster than comparable methods and can be used to add new genomes to an existing call set, allowing sequential use without the need to reanalyse entire collections. Given its robust implementation, inherent absence of reference bias and high accuracy, SKA2 has the potential to become the tool of choice for genotyping bacteria and can help expand the uses of genome data in evolutionary and epidemiological analyses. SKA2 is implemented in Rust and is freely available at https://github.com/bacpop/ska.rust.

bioinformatics↗

bioRxiv2024

Graph-based Nanopore Adaptive Sampling with GNASTy enables sensitive pneumococcal serotyping in complex samples

Serotype surveillance of Streptococcus pneumoniae (the pneumococcus) is critical for understanding the effectiveness of current vaccination strategies. However, existing methods for serotyping are limited in their ability to identify co-carriage of multiple pneumococci and detect novel serotypes. To develop a scalable and portable serotyping method that overcomes these challenges, we employed Nanopore Adaptive Sampling (NAS), an on-sequencer enrichment method which selects for target DNA in real-time, for direct detection of S. pneumoniae in complex samples. Whereas NAS targeting the whole S. pneumoniae genome was ineffective in the presence of non-pathogenic streptococci, the method was both specific and sensitive when targeting the capsular biosynthetic locus (CBL), the operon that determines S. pneumoniae serotype. NAS significantly improved coverage and yield of the CBL relative to sequencing without NAS, and accurately quantified the relative prevalence of serotypes in samples representing co-carriage. To maximise the sensitivity of NAS to detect novel serotypes, we developed and benchmarked a new pangenome-graph algorithm, named GNASTy. We show that GNASTy outperforms the current NAS implementation, which is based on linear genome alignment, when a sample contains a serotype absent from the database of targeted sequences. The methods developed in this work provide an improved approach for novel serotype discovery and routine S. pneumoniae surveillance that is fast, accurate and feasible in low resource settings. GNASTy therefore has the potential to increase the density and coverage of global pneumococcal surveillance. One sentence summaryPangenome graph-based Nanopore Adaptive Sampling, presented in our tool GNASTy, is a sensitive, portable and cost-effective method for Streptococcus pneumoniae surveillance.

genomics↗

bioRxiv2023

PAN-GWES: Pangenome-spanning epistasis and co-selection analysis via de Bruijn graphs

Studies of bacterial adaptation and evolution are hampered by the difficulty of measuring traits such as virulence, drug resistance and transmissibility in large populations. In contrast, it is now feasible to obtain high-quality complete assemblies of many bacterial genomes thanks to scalable and affordable long-read sequencing technology. To exploit this opportunity we introduce a phenotype- and alignment-free method for discovering co-selected and epistatically interacting genomic variation from genome assemblies covering both core and accessory parts of genomes. Our approach uses a compact coloured de Bruijn graph to approximate the intra-genome distances between pairs of loci for a collection of bacterial genomes to account for the impacts of linkage disequilibrium (LD). We demonstrate the versatility of our approach to efficiently identify associations between loci linked with drug resistance and adaptation to the hospital niche in the major human bacterial pathogens Streptococcus pneumoniae and Enterococcus faecalis.

bioinformatics↗

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↗

bioRxiv2023

Accurate and fast graph-based pangenome annotation and clustering with ggCaller

Bacterial genomes differ in both gene content and sequence mutations, which can cause important clinical phenotypic differences such as vaccine escape or antimicrobial resistance. To identify and quantify important variants, all genes within a population must be predicted, functionally annotated and clustered, representing the pangenome. Despite the volume of genome data available, gene prediction and annotation are currently conducted in isolation on individual genomes, which is computationally inefficient and frequently inconsistent across genomes. Here, we introduce the open-source software graph-gene-caller (ggCaller; https://github.com/samhorsfield96/ggCaller). ggCaller combines gene prediction, functional annotation and clustering into a single step using population-wide de Bruijn Graphs, removing redundancy in gene annotation, and resulting in more accurate gene predictions and orthologue clustering. We applied ggCaller to simulated and real-world bacterial genome datasets, comparing it to current state-of-the-art tools. ggCaller is ~50x faster with equivalent or greater accuracy, particularly in datasets with complex sources of error, such as assembly contamination or fragmentation. ggCaller is also an important extension to bacterial genome-wide association studies, enabling querying of annotated graphs for functional analyses. We highlight this application by functionally annotating DNA sequences with significant associations to tetracycline and macrolide resistance in Streptococcus pneumoniae, identifying key resistance determinants that were missed when using only a single reference genome. ggCaller is a novel bacterial genome analysis tool with applications in bacterial epidemiology and evolutionary study.

bioinformatics↗

bioRxiv2022

Post-vaccine epidemiology of serotype 3 pneumococci identifies transformation inhibition through prophage-driven alteration of a non-coding RNA

The respiratory pathogen Streptococcus pneumoniae (the pneumococcus) is a genetically diverse bacterium associated with over 100 immunologically-distinct polysaccharide capsules (serotypes). Polysaccharide conjugate vaccines (PCVs) have successfully eliminated multiple targeted serotypes, yet the mucoid serotype 3 has persisted despite its inclusion in PCV13. This capsule type is predominantly associated with a single globally-disseminated strain, GPSC12 (CC180), which was split into clades by a genomic analysis. Clade I, the most common, rarely underwent transformation, but was typically infected with the prophage {phi}OXC141. Prior to the introduction of PCV13, this clades composition shifted towards a {phi}OXC141-negative subpopulation in a systematically-sampled UK collection. In the post-PCV era, more rapidly-recombining non-Clade I isolates, also {phi}OXC141-negative, have risen in prevalence. The low in vitro transformation efficiency of a Clade I isolate could not be fully explained by the [~]100-fold reduction attributable to the serotype 3 capsule. Accordingly, prophage {phi}OXC141 was found to modify csRNA3, a non-coding RNA that inhibits the induction of transformation. This alteration was identified in [~]30% of all pneumococci, and was particularly common in the unusually-clonal serotype 1 GPSC2 strain. RNA-seq and quantitative reverse transcriptase PCR data demonstrated the altered csRNA3 was more effective at inhibiting production of the competence stimulating peptide pheromone. This interference with the quorum sensing needed to induce competence lowered the rate of spontaneous transformation, reducing the risk of the prophage being deleted by homologous recombination. Hence the selfish prophage-driven alteration of a regulatory RNA limits cell-cell communication and horizontal gene transfer, complicating the interpretation of post-vaccine population dynamics.

microbiology↗

bioRxiv2022

Moonlighting proteins activate transformation in multidrug-resistant Streptococcus pneumoniae epigenetic phase variants

Despite enabling Streptococcus pneumoniae to acquire antibiotic resistance and evade vaccine-induced immunity, transformation occurs at variable rates across pneumococci. Phase variants of isolate RMV7, distinguished by altered methylation patterns driven by the translocating variable restriction-modification (tvr) locus, differed significantly in their transformation efficiencies and biofilm thicknesses. These differences were replicated when the corresponding tvr alleles were introduced into an RMV7 derivative lacking the locus. RNA-seq identified differential expression of the type 1 pilus, causing the variation in biofilm formation, and inhibition of competence induction in the less transformable variant, RMV7domi. This was partly attributable to lower expression of ManLMN in RMV7domi, which promoted competence induction through importing N-acetylglucosamine. This effect was potentiated by orthologues of the gram-negative competence regulatory machinery. Furthermore, a phage-related chromosomal island was more active in RMV7domi, which inhibited transformation by increasing expression of the stress response proteins ClpP and HrcA. However, HrcA increased competence induction in the other variant, with its effects depending on Ca2+ supplementation or heat shock. Hence the heterogeneity in transformation efficiency likely reflects the diverse signalling pathways by which it is affected. This regulatory complexity will modulate population-wide responses to synchronising quorum sensing signals to produce co-ordinated yet stochastic "bet hedging" behaviour.

microbiology↗

bioRxiv2022

Pneumococcal within-host diversity during colonisation, transmission and treatment

Characterising the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition, and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within individual infants and their mothers by deep sequencing whole pneumococcal populations from longitudinal nasopharyngeal samples. We demonstrate deep sequencing has unsurpassed sensitivity for detecting multiple colonisation, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared to gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the childs life. Comprehensive treatment data demonstrated infants were at an elevated risk of both the acquisition, and persistent colonisation, of a multidrug resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonisation imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens.

genomics↗

bioRxiv2021

Genome-wide association, prediction and heritability in bacteria

Advances in whole-genome genotyping and sequencing have allowed genome-wide analyses of association, prediction and heritability in many organisms. However, the application of such analyses to bacteria is still in its infancy, being limited by difficulties including the plasticity of bacterial genomes and their strong population structure. Here we propose, and validate using simulations, a suite of genome-wide analyses for bacteria. We combine methods from human genetics and previous bacterial studies, including linear mixed models, elastic net and LD-score regression, and introduce innovations such as frequency-based allele coding, testing for both insertion/deletion and nucleotide effects and partitioning heritability by genome region. We then analyse three phenotypes of a major human pathogen Streptococcus pneumoniae, including the first analyses of minimum inhibitory concentrations (MIC) for each of two antibiotics, penicillin and ceftriaxone. We show that these are highly heritable leading to high prediction accuracy, which is explained by many genetic associations identified under good control of population structure effects. In the case of ceftriaxone MIC, these results are surprising because none of the isolates was resistant according to the inhibition zone diameter threshold. We estimate that just over half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes around a quarter of the heritability of ceftriaxone MIC. For the within-host survival phenotype carriage duration, no reliable associations were found but we observed moderate heritability and prediction accuracy, indicating a polygenic trait. While generating important new results for S. pneumoniae, we have critically assessed existing methods and introduced innovations that will be useful for future large-scale population genomics studies to help decipher the genetic architecture of bacterial traits. Author summaryGenome-wide association, prediction and heritability analyses in bacteria are beginning to help unravel the genetic underpinnings of traits such as antimicrobial resistance, virulence, within-host survival and transmissibility. Progress to date is limited by challenges including the effects of strong population structure and variable recombination, and the many gaps in sequence alignments including the absence of entire genes in many isolates. More work is required to critically asses and develop methods for bacterial genomics. We address this task here, using a range of existing methods from bacterial and human genetics, such as linear mixed models, elastic net and LD-score regression. Using simulations, we first validate and then adapt these methods to introduce new analyses, including separate assessment of gap and nucleotide effects, a new allele coding for association analyses and a method to partition heritability into genome regions. We analyse within-host survival and two antimicrobial response traits of Streptococcus pneumoniae, identifying many novel associations while demonstrating good control of population structure and accurate prediction. We present both new results for an important pathogen and methodological advances that will be useful in guiding future studies in bacterial population genomics.

genomics↗