Seamless, rapid, and accurate analyses of outbreak genomic data using split k-mer analysis.

Sequence variation observed in populations of pathogens can be used for important public health and evolutionary 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. There is a need for tools that can process this growing volume of bacterial genome data, providing rapid results, but that 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 that 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 with reference-based methods, with no false positives. 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 reanalyze entire collections. With an inherent absence of reference bias, high accuracy, and a robust implementation, SKA2 has the potential to become the tool of choice for genotyping bacteria. SKA2 is implemented in Rust and is freely available as open-source software.

Pangenome-spanning epistasis and coselection 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 high-accuracy long-read sequencing technologies. To exploit this opportunity, we introduce a phenotype- and alignment-free method for discovering coselected and epistatically interacting genomic variation from genome assemblies covering both core and accessory parts of genomes. Our approach uses a compact colored de Bruijn graph to approximate the intragenome 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.

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

Bacterial genomes differ in both gene content and sequence mutations, which underlie extensive phenotypic diversity, including variation in susceptibility to antimicrobials or vaccine-induced immunity. 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). ggCaller combines gene prediction, functional annotation, and clustering into a single workflow 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 data sets containing hundreds or thousands of genomes, comparing it to current state-of-the-art tools. ggCaller has considerable speed-ups with equivalent or greater accuracy, particularly with data sets containing 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 evolution and epidemiology.

Pneumococcal capsule expression is controlled through a conserved, distal cis-regulatory element during infection.

Streptococcus pneumoniae (the pneumococcus) is the major cause of bacterial pneumonia in the US and worldwide. Studies have shown that the differing chemical make-up between serotypes of its most important virulence factor, the capsule, can dictate disease severity. Here we demonstrate that control of capsule synthesis is also critical for infection and facilitated by two broadly conserved transcription factors, SpxR and CpsR, through a distal cis-regulatory element we name the 37-CE. Strikingly, changing only three nucleotides within this sequence is sufficient to render pneumococcus avirulent. Using in vivo and in vitro approaches, we present a model where SpxR interacts as a unique trimeric quaternary structure with the 37-CE to enable capsule repression in the airways. Considering its dramatic effect on infection, variation of the 37-CE between serotypes suggests this molecular switch could be a critical contributing factor to this pathogen's serotype-specific disease outcomes.

Diverse regulatory pathways modulate bet hedging of competence induction in epigenetically-differentiated phase variants of Streptococcus pneumoniae.

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 RMV7domi's lower expression of ManLMN, which promoted competence induction through importing N-acetylglucosamine. This effect was potentiated by analogues of some proteobacterial competence regulatory machinery. Additionally, one of RMV7domi's phage-related chromosomal island was relatively active, 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 and 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.

RCandy: an R package for visualizing homologous recombinations in bacterial genomes.

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.

Pneumococcal Vaccines: Host Interactions, Population Dynamics, and Design Principles.

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.

Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae.

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.

Analysing pneumococcal invasiveness using Bayesian models of pathogen progression rates.

The disease burden attributable to opportunistic pathogens depends on their prevalence in asymptomatic colonisation and the rate at which they progress to cause symptomatic disease. Increases in infections caused by commensals can result from the emergence of "hyperinvasive" strains. Such pathogens can be identified through quantifying progression rates using matched samples of typed microbes from disease cases and healthy carriers. This study describes Bayesian models for analysing such datasets, implemented in an RStan package (https://github.com/nickjcroucher/progressionEstimation). The models converged on stable fits that accurately reproduced observations from meta-analyses of Streptococcus pneumoniae datasets. The estimates of invasiveness, the progression rate from carriage to invasive disease, in cases per carrier per year correlated strongly with the dimensionless values from meta-analysis of odds ratios when sample sizes were large. At smaller sample sizes, the Bayesian models produced more informative estimates. This identified historically rare but high-risk S. pneumoniae serotypes that could be problematic following vaccine-associated disruption of the bacterial population. The package allows for hypothesis testing through model comparisons with Bayes factors. Application to datasets in which strain and serotype information were available for S. pneumoniae found significant evidence for within-strain and within-serotype variation in invasiveness. The heterogeneous geographical distribution of these genotypes is therefore likely to contribute to differences in the impact of vaccination in between locations. Hence genomic surveillance of opportunistic pathogens is crucial for quantifying the effectiveness of public health interventions, and enabling ongoing meta-analyses that can identify new, highly invasive variants.

Fast and flexible bacterial genomic epidemiology with PopPUNK.

The routine use of genomics for disease surveillance provides the opportunity for high-resolution bacterial epidemiology. Current whole-genome clustering and multilocus typing approaches do not fully exploit core and accessory genomic variation, and they cannot both automatically identify, and subsequently expand, clusters of significantly similar isolates in large data sets spanning entire species. Here, we describe PopPUNK (Population Partitioning Using Nucleotide K -mers), a software implementing scalable and expandable annotation- and alignment-free methods for population analysis and clustering. Variable-length k-mer comparisons are used to distinguish isolates' divergence in shared sequence and gene content, which we demonstrate to be accurate over multiple orders of magnitude using data from both simulations and genomic collections representing 10 taxonomically widespread species. Connections between closely related isolates of the same strain are robustly identified, despite interspecies variation in the pairwise distance distributions that reflects species' diverse evolutionary patterns. PopPUNK can process 103-104 genomes in a single batch, with minimal memory use and runtimes up to 200-fold faster than existing model-based methods. Clusters of strains remain consistent as new batches of genomes are added, which is achieved without needing to reanalyze all genomes de novo. This facilitates real-time surveillance with consistent cluster naming between studies and allows for outbreak detection using hundreds of genomes in minutes. Interactive visualization and online publication is streamlined through the automatic output of results to multiple platforms. PopPUNK has been designed as a flexible platform that addresses important issues with currently used whole-genome clustering and typing methods, and has potential uses across bacterial genetics and public health research.

Epidemiological dynamics of bacteriocin competition and antibiotic resistance.

Bacteriocins, toxic peptides involved in the competition between bacterial strains, are extremely diverse. Previous work on bacteriocin dynamics has highlighted the role of non-transitive 'rock-paper-scissors' competition in maintaining the coexistence of different bacteriocin profiles. The focus to date has primarily been on bacteriocin interactions at the within-host scale (i.e. within a single bacterial population). Yet in species such as Streptococcus pneumoniae, with relatively short periods of colonization and limited within-host diversity, ecological outcomes are also shaped by processes at the epidemiological (between-host) scale. Here, we first investigate bacteriocin dynamics and diversity in epidemiological models. We find that in these models, bacteriocin diversity is more readily maintained than in within-host models, and with more possible combinations of coexisting bacteriocin profiles. Indeed, maintenance of diversity in epidemiological models does not require rock-paper-scissors dynamics; it can also occur through a competition-colonization trade-off. Second, we investigate the link between bacteriocin diversity and diversity at antibiotic resistance loci. Previous work has proposed that bacterial duration of colonization modulates the fitness of antibiotic resistance. Due to their inhibitory effects, bacteriocins are a plausible candidate for playing a role in the duration of colonization episodes. We extend the epidemiological model of bacteriocin dynamics to incorporate an antibiotic resistance locus and demonstrate that bacteriocin diversity can indeed maintain the coexistence of antibiotic-sensitive and -resistant strains.

Genome-wide epistasis and co-selection study using mutual information.

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.

Lineage-specific evolution and gene flow in Listeria monocytogenes are independent of bacteriophages.

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.

Bayesian inference of ancestral dates on bacterial phylogenetic trees.

The sequencing and comparative analysis of a collection of bacterial genomes from a single species or lineage of interest can lead to key insights into its evolution, ecology or epidemiology. The tool of choice for such a study is often to build a phylogenetic tree, and more specifically when possible a dated phylogeny, in which the dates of all common ancestors are estimated. Here, we propose a new Bayesian methodology to construct dated phylogenies which is specifically designed for bacterial genomics. Unlike previous Bayesian methods aimed at building dated phylogenies, we consider that the phylogenetic relationships between the genomes have been previously evaluated using a standard phylogenetic method, which makes our methodology much faster and scalable. This two-step approach also allows us to directly exploit existing phylogenetic methods that detect bacterial recombination, and therefore to account for the effect of recombination in the construction of a dated phylogeny. We analysed many simulated datasets in order to benchmark the performance of our approach in a wide range of situations. Furthermore, we present applications to three different real datasets from recent bacterial genomic studies. Our methodology is implemented in a R package called BactDating which is freely available for download at https://github.com/xavierdidelot/BactDating.

Excision-reintegration at a pneumococcal phase-variable restriction-modification locus drives within- and between-strain epigenetic differentiation and inhibits gene acquisition.

Phase-variation of Type I restriction-modification systems can rapidly alter the sequence motifs they target, diversifying both the epigenetic patterns and endonuclease activity within clonally descended populations. Here, we characterize the Streptococcus pneumoniae SpnIV phase-variable Type I RMS, encoded by the translocating variable restriction (tvr) locus, to identify its target motifs, mechanism and regulation of phase variation, and effects on exchange of sequence through transformation. The specificity-determining hsdS genes were shuffled through a recombinase-mediated excision-reintegration mechanism involving circular intermediate molecules, guided by two types of direct repeat. The rate of rearrangements was limited by an attenuator and toxin-antitoxin system homologs that inhibited recombinase gene transcription. Target motifs for both the SpnIV, and multiple Type II, MTases were identified through methylation-sensitive sequencing of a panel of recombinase-null mutants. This demonstrated the species-wide diversity observed at the tvr locus can likely specify nine different methylation patterns. This will reduce sequence exchange in this diverse species, as the native form of the SpnIV RMS was demonstrated to inhibit the acquisition of genomic islands by transformation. Hence the tvr locus can drive variation in genome methylation both within and between strains, and limits the genomic plasticity of S. pneumoniae.

Evolution of antibiotic resistance is linked to any genetic mechanism affecting bacterial duration of carriage.

Understanding how changes in antibiotic consumption affect the prevalence of antibiotic resistance in bacterial pathogens is important for public health. In a number of bacterial species, including Streptococcus pneumoniae, the prevalence of resistance has remained relatively stable despite prolonged selection pressure from antibiotics. The evolutionary processes allowing the robust coexistence of antibiotic sensitive and resistant strains are not fully understood. While allelic diversity can be maintained at a locus by direct balancing selection, there is no evidence for such selection acting in the case of resistance. In this work, we propose a mechanism for maintaining coexistence at the resistance locus: linkage to a second locus that is under balancing selection and that modulates the fitness effect of resistance. We show that duration of carriage plays such a role, with long duration of carriage increasing the fitness advantage gained from resistance. We therefore predict that resistance will be more common in strains with a long duration of carriage and that mechanisms maintaining diversity in duration of carriage will also maintain diversity in antibiotic resistance. We test these predictions in S. pneumoniae and find that the duration of carriage of a serotype is indeed positively correlated with the prevalence of resistance in that serotype. These findings suggest heterogeneity in duration of carriage is a partial explanation for the coexistence of sensitive and resistant strains and that factors determining bacterial duration of carriage will also affect the prevalence of resistance.

Diverse evolutionary patterns of pneumococcal antigens identified by pangenome-wide immunological screening.

Characterizing the immune response to pneumococcal proteins is critical in understanding this bacterium's epidemiology and vaccinology. Probing a custom-designed proteome microarray with sera from 35 healthy US adults revealed a continuous distribution of IgG affinities for 2,190 potential antigens from the species-wide pangenome. Reproducibly elevated IgG binding was elicited by 208 "antibody binding targets" (ABTs), which included 109 variants of the diverse pneumococcal surface proteins A and C (PspA and PspC) and zinc metalloprotease A and B (ZmpA and ZmpB) proteins. Functional analysis found ABTs were enriched in motifs for secretion and cell surface association, with extensive representation of cell wall synthesis machinery, adhesins, transporter solute-binding proteins, and degradative enzymes. ABTs were associated with stronger evidence for evolving under positive selection, although this varied between functional categories, as did rates of diversification through recombination. Particularly rapid variation was observed at some immunogenic accessory loci, including a phage protein and a phase-variable glycosyltransferase ubiquitous among the diverse set of genomic islands encoding the serine-rich PsrP glycoprotein. Nevertheless, many antigens were conserved in the core genome, and strains' antigenic profiles were generally stable. No strong evidence was found for any epistasis between antigens driving population dynamics, or redundancy between functionally similar accessory ABTs, or age stratification of antigen profiles. These results highlight the paradox of why substantial variation is observed in only a subset of epitopes. This result may indicate only some interactions between immunoglobulins and ABTs clear pneumococcal colonization or that acquired immunity to pneumococci is an accumulation of individually weak responses to ABTs evolving under different levels of functional constraint.

Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis.

Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein-protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.

Methylation Warfare: Interaction of Pneumococcal Bacteriophages with Their Host.

Virus-host interactions are regulated by complex coevolutionary dynamics. In Streptococcus pneumoniae, phase-variable type I restriction-modification (R-M) systems are part of the core genome. We hypothesized that the ability of the R-M systems to switch between six target DNA specificities also has a key role in preventing the spread of bacteriophages. Using the streptococcal temperate bacteriophage SpSL1, we show that the variants of both the SpnIII and SpnIV R-M systems are able to restrict invading bacteriophage with an efficiency approximately proportional to the number of target sites in the bacteriophage genome. In addition to restriction of lytic replication, SpnIII also led to abortive infection in the majority of host cells. During lytic infection, transcriptional analysis found evidence of phage-host interaction through the strong upregulation of the nrdR nucleotide biosynthesis regulon. During lysogeny, the phage had less of an effect on host gene regulation. This research demonstrates a novel combined bacteriophage restriction and abortive infection mechanism, highlighting the importance that the phase-variable type I R-M systems have in the multifunctional defense against bacteriophage infection in the respiratory pathogen S. pneumoniaeIMPORTANCE With antimicrobial drug resistance becoming an increasing burden on human health, much attention has been focused on the potential use of bacteriophages and their enzymes as therapeutics. However, the investigations into the physiology of the complex interactions of bacteriophages with their hosts have attracted far less attention, in comparison. This work describes the molecular characterization of the infectious cycle of a bacteriophage in the important human pathogen Streptococcus pneumoniae and explores the intricate relationship between phase-variable host defense mechanisms and the virus. This is the first report showing how a phase-variable type I restriction-modification system is involved in bacteriophage restriction while it also provides an additional level of infection control through abortive infection.

The Contribution of Genetic Variation of Streptococcus pneumoniae to the Clinical Manifestation of Invasive Pneumococcal Disease.

Background: Different clinical manifestations of invasive pneumococcal disease (IPD) have thus far mainly been explained by patient characteristics. Here we studied the contribution of pneumococcal genetic variation to IPD phenotype. Methods: The index cohort consisted of 349 patients admitted to 2 Dutch hospitals between 2000-2011 with pneumococcal bacteremia. We performed genome-wide association studies to identify pneumococcal lineages, genes, and allelic variants associated with 23 clinical IPD phenotypes. The identified associations were validated in a nationwide (n = 482) and a post-pneumococcal vaccination cohort (n = 121). The contribution of confirmed pneumococcal genotypes to the clinical IPD phenotype, relative to known clinical predictors, was tested by regression analysis. Results: Among IPD patients, the presence of pneumococcal gene slaA was a nationwide confirmed independent predictor of meningitis (odds ratio [OR], 10.5; P = .001), as was sequence cluster 9 (serotype 7F: OR, 3.68; P = .057). A set of 4 pneumococcal genes co-located on a prophage was a confirmed independent predictor of 30-day mortality (OR, 3.4; P = .003). We could detect the pneumococcal variants of concern in these patients' blood samples. Conclusions: In this study, knowledge of pneumococcal genotypic variants improved the clinical risk assessment for detrimental manifestations of IPD. This provides us with novel opportunities to target, anticipate, or avert the pathogenic effects related to particular pneumococcal variants, and indicates that information on pneumococcal genotype is important for the diagnostic and treatment strategy in IPD. Ongoing surveillance is warranted to monitor the clinical value of information on pneumococcal variants in dynamic microbial and susceptible host populations.