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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 inStreptococcus 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.

Background The respiratory pathogen Streptococcus pneumoniae (the pneumococcus) is a genetically diverse bacterium associated with over 101 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 (clonal complex 180). Methods A genomic epidemiology study combined previous surveillance datasets of serotype 3 pneumococci to analyse the population structure, dynamics, and differences in rates of diversification within GPSC12 during the period of PCV introductions. Transcriptomic analyses, whole genome sequencing, mutagenesis, and electron microscopy were used to characterise the phenotypic impact of loci hypothesised to affect this strain’s evolution. Results GPSC12 was split into clades by a genomic analysis. Clade I, the most common, rarely underwent transformation, but was typically infected with the prophage ϕOXC141. Prior to the introduction of PCV13, this clade’s composition shifted towards a ϕOXC141-negative subpopulation in a systematically sampled UK collection. In the post-PCV13 era, more rapidly recombining non-Clade I isolates, also ϕOXC141-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 ϕOXC141 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 experiments using a genetically tractable pneumococcus demonstrated the altered csRNA3 was more effective at inhibiting production of the competence-stimulating peptide pheromone. This resulted in a reduction in the induction of competence for transformation. Conclusion This interference with the quorum sensing needed to induce competence reduces 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.

The isolation of Streptococcus pneumoniae serotypes in systemic tissues of patients with invasive disease versus the nasopharynx of healthy individuals with asymptomatic carriage varies widely. Some serotypes are hyper-invasive, particularly serotype 1, but the underlying genetics remain poorly understood due to the rarity of carriage isolates, reducing the power of comparison with invasive isolates. Here, we use a well-controlled genome-wide association study to search for genetic variation associated with invasiveness of serotype 1 pneumococci from a serotype 1 endemic setting in Africa. We found no consensus evidence that certain genomic variation is overrepresented among isolates from patients with invasive disease than asymptomatic carriage. Overall, the genomic variation explained negligible phenotypic variability, suggesting a minimal effect on the disease status. Furthermore, changes in lineage distribution were seen with lineages replacing each other over time, highlighting the importance of continued pathogen surveillance. Our findings suggest that the hyper-invasiveness is an intrinsic property of the serotype 1 strains, not specific for a “disease-associated” subpopulation disproportionately harboring unique genomic variation.

Streptococcus pneumoniae is a major human pathogen that can cause severe invasive diseases such as pneumonia, septicaemia and meningitis. Young children are at a particularly high risk, with an estimated 3–4 million cases of severe disease and between 300 000 and 500 000 deaths attributable to pneumococcal disease each year. The haemolytic toxin pneumolysin (Ply) is a primary virulence factor for this bacterium, yet despite its key role in pathogenesis, immune evasion and transmission, the regulation of Ply production is not well defined. Using a genome-wide association approach, we identified a large number of potential affectors of Ply activity, including a gene acquired horizontally on the antibiotic resistance-conferring Integrative and Conjugative Element (ICE) ICESp23FST81. This gene encodes a novel modular protein, ZomB, which has an N-terminal UvrD-like helicase domain followed by two Cas4-like domains with potent ATP-dependent nuclease activity. We found the regulatory effect of ZomB to be specific for the ply operon, potentially mediated by its high affinity for the BOX repeats encoded therein. Using a murine model of pneumococcal colonization, we further demonstrate that a ZomB mutant strain colonizes both the upper respiratory tract and lungs at higher levels when compared to the wild-type strain. While the antibiotic resistance-conferring aspects of ICESp23FST81 are often credited with contributing to the success of the S. pneumoniae lineages that acquire it, its ability to control the expression of a major virulence factor implicated in bacterial transmission is also likely to have played an important role.

Transformation of Streptococcus pneumoniae GPSC1 has enabled vaccine evasion and the acquisition of antibiotic resistance. Epigenetic phase variants of GPSC1 isolate RMV7, differentiated by rearrangements at the tvr restriction-modification locus, differed ∼100-fold in their transformation efficiency. This variation was recapitulated in knock-in mutants of the relevant tvr alleles. RNA-seq showed the difference was due to blocking of the early competence regulatory cascade. The more transformable variant upregulated expression of manLMN, encoding a carbon source importer. This was shown to be necessary for efficient competence induction, despite being dispensable for growth in rich media. Transformation was promoted by import of N-acetylglucosamine, which activated competence through an orthologue of the gram-negative competence regulator TfoX, and an enzyme likely involved in nucleotide-mediated signalling. A mobile genetic element was more active in the less transformable variant, which limited competence induction through inhibiting CIRCE motif binding by the chaperone regulator HrcA. Correspondingly, both heat shock and decreased Ca2+ concentrations reduced competence by limiting HrcA binding regulatory sequence motifs. Hence both ManLMN and HrcA moonlighted as activators of competence. Such proteins may be important in potentiating horizontal DNA exchange, as selection on their primary function likely constrains them from mutating into alleles that selfishly downregulate transformation.

Whole-genome sequencing has facilitated genome-wide analyses of association, prediction and heritability in many organisms. However, such analyses in bacteria are still in their infancy, being limited by difficulties including genome plasticity and strong population structure. Here we propose a suite of methods including linear mixed models, elastic net and LD-score regression, adapted to bacterial traits using innovations such as frequency-based allele coding, both insertion/deletion and nucleotide testing and heritability partitioning. We compare and validate our methods against the current state-of-art using simulations, and analyse three phenotypes of the major human pathogen Streptococcus pneumoniae, including the first analyses of minimum inhibitory concentrations (MIC) for penicillin and ceftriaxone. We show that the MIC traits are highly heritable with high prediction accuracy, explained by many genetic associations under good population structure control. In ceftriaxone MIC, this is surprising because none of the isolates are resistant as per the inhibition zone criteria. We estimate that half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes a quarter of the ceftriaxone MIC heritability. For the within-host carriage duration phenotype, no associations were observed, but the moderate heritability and prediction accuracy indicate a moderately polygenic trait.

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 child’s 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.

Summary Homologous recombination is an important evolutionary process in bacteria and other prokaryotes, which increases genomic sequence diversity and can facilitate adaptation. Several methods and tools have been developed to detect genomic regions recently affected by recombination. Exploration and visualization of such recombination events can reveal valuable biological insights, but it remains challenging. Here, we present RCandy, a platform-independent R package for rapid, simple and flexible visualization of recombination events in bacterial genomes. Availability and implementation RCandy is an R package freely available for use under the MIT license. It is platform-independent and has been tested on Windows, Linux and MacOSX. The source code comes together with a detailed vignette available on GitHub at https://github.com/ChrispinChaguza/RCandy. Supplementary information Supplementary data are available at Bioinformatics online.

Antimicrobial resistance in enteric or urinary Escherichia coli is a risk factor for invasive E. coli infections. Due to widespread trimethoprim resistance amongst urinary E. coli and increased bacteraemia incidence, a national recommendation to prescribe nitrofurantoin for uncomplicated urinary tract infection was made in 2014. Nitrofurantoin resistance is reported in E. coli isolates in the UK, however, mechanisms underpinning nitrofurantoin resistance in these isolates remain unknown. This study aimed to identify the genetic basis of nitrofurantoin resistance in urinary E. coli isolates collected from north west London and then elucidate resistance-associated genetic alterations in available UK E. coli genomes. As a result, an algorithm was developed to predict nitrofurantoin susceptibility. Deleterious mutations and gene-inactivating insertion sequences in chromosomal nitroreductase genes nfsA and/or nfsB were identified in genomes of nine confirmed nitrofurantoin-resistant urinary E. coli isolates and additional 11 E. coli isolates that were highlighted by the prediction algorithm and subsequently validated to be nitrofurantoin-resistant. Eight categories of allelic changes in nfsA, nfsB, and the associated gene ribE were detected in 12412 E. coli genomes from the UK. Evolutionary analysis of these three genes revealed homoplasic mutations and explained the previously reported order of stepwise mutations. The mobile gene complex oqxAB, which is associated with reduced nitrofurantoin susceptibility, was identified in only one of the 12412 genomes. In conclusion, mutations and insertion sequences in nfsA and nfsB were leading causes of nitrofurantoin resistance in UK E. coli . As nitrofurantoin exposure increases in human populations, the prevalence of nitrofurantoin resistance in carriage E. coli isolates and those from urinary and bloodstream infections should be monitored.

Whole-genome sequencing has facilitated genome-wide analyses of association, prediction and heritability in many organisms. However, such analyses in bacteria are still in their infancy, being limited by difficulties including genome plasticity and strong population structure. Here we propose a suite of methods including linear mixed models, elastic net and LD-score regression, adapted to bacterial traits using innovations such as frequency-based allele coding, both insertion/deletion and nucleotide testing and heritability partitioning. We compare and validate our methods against the current state-of-art using simulations, and analyse three phenotypes of the major human pathogen

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.

Background: Pneumococcal conjugate vaccines have reduced the incidence of invasive pneumococcal disease, caused by vaccine serotypes, but non-vaccine-serotypes remain a concern. We used whole genome sequencing to study pneumococcal serotype, antibiotic resistance and invasiveness, in the context of genetic background. Methods: Our dataset of 13,454 genomes, combined with four published genomic datasets, represented Africa (40%), Asia (25%), Europe (19%), North America (12%), and South America (5%). These 20,027 pneumococcal genomes were clustered into lineages using PopPUNK, and named Global Pneumococcal Sequence Clusters (GPSCs). From our dataset, we additionally derived serotype and sequence type, and predicted antibiotic sensitivity. We then measured invasiveness using odds ratios that relating prevalence in invasive pneumococcal disease to carriage. Findings: The combined collections (n = 20,027) were clustered into 621 GPSCs. Thirty-five GPSCs observed in our dataset were represented by >100 isolates, and subsequently classed as dominant-GPSCs. In 22/35 (63%) of dominant-GPSCs both non-vaccine serotypes and vaccine serotypes were observed in the years up until, and including, the first year of pneumococcal conjugate vaccine introduction.Penicillin and multidrug resistance were higher (p

Antimicrobial resistance in enteric or urinary Escherichia coli is a risk factor for invasive E. coli infections. Due to widespread trimethoprim resistance amongst urinary E. coli and increased bacteraemia incidence, a national recommendation to prescribe nitrofurantoin for uncomplicated urinary tract infection was made in 2018. Nitrofurantoin resistance is reported in E. coli isolates in the UK. However, mechanisms underpinning nitrofurantoin resistance in these isolates remain unknown. This study aimed to identify genetic determinants of nitrofurantoin resistance in a local E. coli collection and assess their prevalence in a larger dataset of E. coli genomes. Deleterious point mutations and gene-inactivating insertion sequences in both chromosomal nitroreductase genes nfsA and nfsB were identified in genomes of nine nitrofurantoin-resistant urinary E. coli isolates collected from north west London. Eight types of genetic alterations were identified when comparing sequences of nfsA, nfsB, and the associated gene ribE in 12,412 E. coli genomes collected from across the UK. Evolutionary analysis revealed homoplasic mutations and explained the order of stepwise mutations. An algorithm was developed to predict nitrofurantoin susceptibility and predictions for 20 accessible isolates were experimentally validated. Only one genome carrying oqxAB, a mobile gene complex associated with reduced nitrofurantoin susceptibility, was identified. In conclusion, mutations and insertion sequences in nfsA and nfsB are leading causes of nitrofurantoin resistance in UK E. coli. As nitrofurantoin exposure increases in human populations, the prevalence of nitrofurantoin resistance in carriage E. coli isolates and those from urinary and bloodstream infections should be monitored.ImportanceThis study expands knowledge about the genetic basis of nitrofurantoin resistance in E. coli isolates using whole-genome sequencing and genomic analysis. We report novel and previously known deleterious mutations of chromosomal genes nfsA, nfsB, and ribE as well as the interruption of nfsA and nfsB by insertion sequences, recapitulating the roles of oxygen-insensitive nitroreductases in the development of nitrofurantoin resistance in E. coli. We revealed and categorised the genotypic diversity in these three genes in a large collection of UK E. coli genomes. A scoring algorithm is provided to predict nitrofurantoin susceptibility from genotypes. Our predictions suggest that acquired nitrofurantoin resistance is not of immediate concern in the UK. However, experimental validation of predictions suggested the involvement of mechanisms other than alterations in nfsA, nfsB, or ribE in determining nitrofurantoin susceptibility, emphasising the need for monitoring nitrofurantoin resistance amongst E. coli.

The evolutionary histories of the antibiotic-resistantStreptococcus pneumoniaelineages PMEN3 and PMEN9 were reconstructed using global collections of genomes. In PMEN3, one resistant clade spread worldwide, and underwent 25 serotype switches, enabling evasion of vaccine-induced immunity. In PMEN9, only 9 switches were detected, and multiple resistant lineages emerged independently and circulated locally. In Germany, PMEN9’s expansion correlated significantly with the macrolide:penicillin consumption ratio. These isolates were penicillin sensitive but macrolide resistant, through a homologous recombination that integrated Tn1207.1into a competence gene, preventing further diversification via transformation. Analysis of a species-wide dataset found 183 acquisitions of macrolide resistance, and multiple gains of the tetracycline-resistant transposon Tn916, through homologous recombination, often originating in other streptococcal species. Consequently, antibiotic selection preserves atypical recom- bination events that cause sequence divergence and structural variation throughout theS. pneumoniaechromosome. These events reveal the genetic exchanges between species normally counter-selected until perturbed by clinical interventions.

Summary: Background: The clonal diversity underpinning trends in multidrug resistant Escherichia coli causing bloodstream infections remains uncertain. We aimed to determine the contribution of individual clones to resistance over time, using large-scale genomics-based molecular epidemiology. Methods: This was a longitudinal, E coli population, genomic, cohort study that sampled isolates from 22 512 E coli bloodstream infections included in the Norwegian surveillance programme on resistant microbes (NORM) from 2002 to 2017. 15 of 22 laboratories were able to share their isolates, and the first 22·5% of isolates from each year were requested. We used whole genome sequencing to infer the population structure (PopPUNK), and we investigated the clade composition of the dominant multidrug resistant clonal complex (CC)131 using genetic markers previously reported for sequence type (ST)131, effective population size (BEAST), and presence of determinants of antimicrobial resistance (ARIBA, PointFinder, and ResFinder databases) over time. We compared these features between the 2002–10 and 2011–17 time periods. We also compared our results with those of a longitudinal study from the UK done between 2001 and 2011. Findings: Of the 3500 isolates requested from the participating laboratories, 3397 (97·1%) were received, of which 3254 (95·8%) were successfully sequenced and included in the analysis. A significant increase in the number of multidrug resistant CC131 isolates from 71 (5·6%) of 1277 in 2002–10 to 207 (10·5%) of 1977 in 2011–17 (p

Streptococcus pneumoniae is a significant cause of otitis media, pneumonia, and meningitis. Only seven of the approximately 100 serotypes were initially included in the pneumococcal polysaccharide conjugate vaccine (PCV) in 2000 before it was expanded in subsequent years. Although the invasive pneumococcal disease (IPD) incidence due to vaccine serotypes (VT) has declined, partial replacement by non-vaccine serotypes (NVT) was observed following widespread vaccine uptake. We conducted a trend analysis assembling the available evidence for PCV impact on European, North American and Australian national IPD. Significant effectiveness against VT IPD in infants was observed, although the impact on national IPD incidence varied internationally due to serotype replacement. Currently, NVT serotypes 8, 9N, 15A and 23B are increasing in the countries assessed, although a variety of other NVTs are affecting each country and age group. Despite these common emerging serotypes, there has not been a dominant IPD serotype post-vaccination as there was pre-vaccination (serotype 14) or post-PCV7 (serotype 19A), suggesting that future vaccines with additional serotypes will be less effective at targeting and reducing IPD in global populations than previous PCVs. The rise of diverse NVTs in all settings’ top-ranked IPD-causing serotypes emphasizes the urgent need for surveillance data on serotype distribution and serotype-specific invasiveness post-vaccination to facilitate decision making concerning both expanding current vaccination programmes and increasing vaccine valency.

Streptococcus pneumoniae can be divided into many strains, each a distinct set of isolates sharing similar core and accessory genomes, which co-circulate within the same hosts. Previous analyses suggested the short-term vaccine-associated dynamics of S. pneumoniae strains may be mediated through multi-locus negative frequency-dependent selection (NFDS), which maintains accessory loci at equilibrium frequencies. Long-term simulations demonstrated NFDS stabilised clonally-evolving multi-strain populations through preventing the loss of variation through drift, based on polymorphism frequencies, pairwise genetic distances and phylogenies. However, allowing symmetrical recombination between isolates evolving under multi-locus NFDS generated unstructured populations of diverse genotypes. Replication of the observed data improved when multi-locus NFDS was combined with recombination that was instead asymmetrical, favouring deletion of accessory loci over insertion. This combination separated populations into strains through outbreeding depression, resulting from recombinants with reduced accessory genomes having lower fitness than their parental genotypes. Although simplistic modelling of recombination likely limited these simulations’ ability to maintain some properties of genomic data as accurately as those lacking recombination, the combination of asymmetrical recombination and multi-locus NFDS could restore multi-strain population structures from randomised initial populations. As many bacteria inhibit insertions into their chromosomes, this combination may commonly underlie the co-existence of strains within a niche.

Knowledge of pneumococcal lineages, their geographic distribution and antibiotic resistance patterns, can give insights into global pneumococcal disease. We provide interactive bioinformatic outputs to explore such topics, aiming to increase dissemi-nation of genomic insights to the wider community, without the need for specialist training. We prepared 12 country-specific phylogenetic snapshots, and international phylogenetic snapshots of 73 common Global Pneumococcal Sequence Clusters (GPSCs) previously defined using PopPUNK, and present them in Microreact. Gene presence and absence defined using Roary, and recombination profiles derived from Gubbins are presented in Phandango for each GPSC. Temporal phylogenetic signal was assessed for each GPSC using BactDating. We provide examples of how such resources can be used. In our example use of a country-specific phylogenetic snapshot we determined that serotype 14 was observed in nine unrelated genetic backgrounds in South Africa. The international phylogenetic snapshot of GPSC9, in which most serotype 14 isolates from South Africa were observed, highlights that there were three independent sub-clusters represented by South African serotype 14 isolates. We estimated from the GPSC9-dated tree that the sub-clusters were each established in South Africa during the 1980s. We show how recombination plots allowed the identification of a 20 kb recombination spanning the capsular polysaccharide locus within GPSC97. This was consistent with a switch from serotype 6A to 19A estimated to have occured in the 1990s from the GPSC97-dated tree. Plots of gene presence/absence of resistance genes (tet, erm, cat) across the GPSC23 phylogeny were consistent with acquisition of a composite transposon. We estimated from the GPSC23-dated tree that the acquisition occurred between 1953 and 1975. Finally, we demonstrate the assignment of GPSC31 to 17 externally generated pneumococcal serotype 1 assemblies from Utah via Pathogenwatch. Most of the Utah isolates clustered within GPSC31 in a USA-specific clade with the most recent common ancestor estimated between 1958 and 1981. The resources we have provided can be used to explore to data, test hypothesis and generate new hypotheses. The accessible assignment of GPSCs allows others to contextualize their own collections beyond the data presented here.

openaire: EC/H2020/742158/EU//SCARABEE Covariance-based discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level covariation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria. SpydrPick incorporates an efficient correction for population structure, which adjusts for the phylogenetic signal in the data without requiring an explicit phylogenetic tree. We also introduce a new type of visualization of the results similar to the Manhattan plots used in genome-wide association studies, which enables rapid exploration of the identified signals of co-evolution. Simulations demonstrate the usefulness of our method and give some insight to when this type of analysis is most likely to be successful. Application of the method to large population genomic datasets of two major human pathogens, Streptococcus pneumoniae and Neisseria meningitidis, revealed both previously identified and novel putative targets of co-selection related to virulence and antibiotic resistance, highlighting the potential of this approach to drive molecular discoveries, even in the absence of phenotypic data.

Streptococcus pneumoniae (the pneumococcus) is a nasopharyngeal commensal and respiratory pathogen. Most isolates express a capsule, the species-wide diversity of which has been immunologically classified into ∼100 serotypes. Capsule polysaccharides have been combined into multivalent vaccines widely used in adults, but the T cell independence of the antibody response means they are not protective in infants. Polysaccharide conjugate vaccines (PCVs) trigger a T cell–dependent response through attaching a carrier protein to capsular polysaccharides. The immune response stimulated by PCVs in infants inhibits carriage of vaccine serotypes (VTs), resulting in population-wide herd immunity. These were replaced in carriage by non-VTs. Nevertheless, PCVs drove reductions in infant pneumococcal disease, due to the lower mean invasiveness of the postvaccination bacterial population; age-varying serotype invasiveness resulted in a smaller reduction in adult disease. Alternative vaccines being tested in trials are designed to provide species-wide protection through stimulating innate and cellular immune responses, alongside antibodies to conserved antigens.

Predicting how pathogen populations will change over time is challenging. Such has been the case with Streptococcus pneumoniae, an important human pathogen, and the pneumococcal conjugate vaccines (PCVs), which target only a fraction of the strains in the population. Here, we use the frequencies of accessory genes to predict changes in the pneumococcal population after vaccination, hypothesizing that these frequencies reflect negative frequency-dependent selection (NFDS) on the gene products. We find that the standardized predicted fitness of a strain, estimated by an NFDS-based model at the time the vaccine is introduced, enables us to predict whether the strain increases or decreases in prevalence following vaccination. Further, we are able to forecast the equilibrium post-vaccine population composition and assess the invasion capacity of emerging lineages. Overall, we provide a method for predicting the impact of an intervention on pneumococcal populations with potential application to other bacterial pathogens in which NFDS is a driving force., Predicting how pathogen populations will change over time is challenging. This study predicts population changes in human pathogen Streptococcus pneumoniae after vaccination, using a model of negative frequency-dependent selection acting on accessory gene products.

Background: The clonal diversity underpinning trends in multi-drug resistant (MDR) E. coli causing bloodstream infections (BSI) remain uncertain. We determine these from the largest longitudinal E. coli population genomic study conducted to date. Methods: E. coli from BSI collected by the Norwegian surveillance program on resistant microbes were randomly sampled between 2002-2017. The 3254 isolates, representing ~7% of annual cases and all health regions, were whole-genome sequenced. Findings: The equilibrium of major clones was disrupted by the increase of MDR clonal complex (CC)131 and its component clades. CC131 was the dominant contributor to increases in ESBL prevalence and fluoroquinolone resistance. Clade A increased from 2002, whilst the global MDR clade C2 was not observed until 2007. Frequent de novo acquisition of both blaCTX-M ESBL genes in clades A and C1, and of fluoroquinolone resistance in clade A were observed. We estimated exponential increases in the effective population sizes of clades A, C1 and C2 occurring in the mid-2000’s, and in clade B a decade earlier. The rate of increase in clade A was nearly ten-fold that of C2, with clade A over-represented in Norway compared to a UK study by Kallonen et al. Interpretation: Despite Norway's low antimicrobial use, multiple clades of CC131 rapidly established themselves, with non-C2 clades acquiring resistance to important antimicrobial classes. This suggests that antimicrobial resistance is a consequence of, rather than a determinant of success. This study demonstrates the importance of genomic surveillance in uncovering complex ecology underlying MDR dissemination and competition, within clones of priority pathogens. Funding: This work was supported by a Trond Mohn Foundation AMR grant TMS2019TMT04 (R.G., A.P., J.C., O.S., P.J.) and ERC grant 742158 (J.C.). Declaration of Interests: The authors report no conflicts of interest. Ethics Approval Statement: Data in NORM are disidentified. Ethical approval was not required after evaluation by the Regional Ethical Committee (REC North ref: 93528).

Listeria monocytogenes is a foodborne pathogen causing systemic infection with high mortality. To allow efficient tracking of outbreaks a clear definition of the genomic signature of a cluster of related isolates is required, but lineage-specific characteristics call for a more detailed understanding of evolution. In our work, we used core genome MLST (cgMLST) to identify new outbreaks combined to core genome SNP analysis to characterize the population structure and gene flow between lineages. Whilst analysing differences between the four lineages of L. monocytogenes we have detected differences in the recombination rate, and interestingly also divergence in the SNP differences between sub-lineages. In addition, the exchange of core genome variation between the lineages exhibited a distinct pattern, with lineage III being the best donor for horizontal gene transfer. Whilst attempting to link bacteriophage-mediated transduction to observed gene transfer, we found an inverse correlation between phage presence in a lineage and the extent of recombination. Irrespective of the profound differences in recombination rates observed between sub-lineages and lineages, we found that the previously proposed cut-off of 10 allelic differences in cgMLST can be still considered valid for the definition of a foodborne outbreak cluster of L. monocytogenes.

Streptococcus pneumoniae (the pneumococcus) is a common nasopharyngeal commensal that can cause invasive pneumococcal disease (IPD). Each component of current protein–polysaccharide conjugate vaccines (PCVs) generally induces immunity specific to one of the approximately 100 pneumococcal serotypes, and typically eliminates it from carriage and IPD through herd immunity. Overall carriage rates remain stable owing to replacement by non-PCV serotypes. Consequently, the net change in IPD incidence is determined by the relative invasiveness of the pre- and post-PCV-carried pneumococcal populations. In the present study, we identified PCVs expected to minimize the post-vaccine IPD burden by applying Bayesian optimization to an ecological model of serotype replacement that integrated epidemiological and genomic data. We compared optimal formulations for reducing infant-only or population-wide IPD, and identified potential benefits to including non-conserved pneumococcal carrier proteins. Vaccines were also devised to minimize IPD resistant to antibiotic treatment, despite the ecological model assuming that resistance levels in the carried population would be preserved. We found that expanding infant-administered PCV valency is likely to result in diminishing returns, and that complementary pairs of infant- and adult-administered vaccines could be a superior strategy. PCV performance was highly dependent on the circulating pneumococcal population, further highlighting the advantages of a diversity of anti-pneumococcal vaccination strategies. Here the authors have developed a framework to predict which Streptococcus pneumoniae serotypes would be best targeted by vaccination, of children and adults, to prevent the post-vaccine emergence of similarly virulent strains, thereby minimizing the pneumococcal disease burden.

Penicillin-non-susceptible Streptococcus pneumoniae (PNSP) were first detected in the 1960s, and are now common worldwide, predominantly through the international spread of a limited number of strains. Extant PNSP are characterized by mosaic pbp2x, pbp2b and pbp1a genes generated by interspecies recombinations, with the extent of these alterations determining the range and concentrations of β-lactams to which the genotype is non-susceptible. The complexity of the genetics underlying these phenotypes has been the subject of both molecular microbiology and genome-wide association and epistasis analyses. Such studies can aid our understanding of PNSP evolution and help improve the already highly-performing bioinformatic methods capable of identifying PNSP from genomic surveillance data.